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RT1050 HAB Encrypted Image Generation and Analysis 1, Introduction      The NXP RT series can support multiple boot modes, it incluses: unsigned image mode, HAB signed image mode, HAB encryption image mode, and BEE encryption  image mode.       In order to understand the specific structure of the HAB encryption app, this article will generate a non-XIP app image, then generate the relevant burning file through the elftosb.exe tool in the flashloader i.MX-RT1050, and use MFGTOOL to enter the serial download mode to download the .sb file.       This article will focus on the download steps of RT1050 HAB encryption related operations, and analyze the structure of the HAB encrypted app image.     2, RT1050 HAB Encypted Operation Procedure At first, we analyze the steps of MFGtool burning, which files are needed, so as to give specific preparation, open the ucl2.xml file in the following path of the flashloader: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\mfgtools-rel\Profiles\MXRT105X\OS Firmware Because we need to use the HAB encrypated boot mode, then we will use MXRT105X-SecureBoot, from the ucl2.xml file, we will find the following related code: Fig 1. MXRT1050-SecureBoot structure As you can see from the above, to implement the secure boot of RT1050, you need to prepare these three files: ivt_flashlloader_signed.bin: it is the signed flashloader binary file enable_hab.sb: it is used to modify the SRK and HABmode in the fuse map boot_image.sb: HAB encrypted app program file       Here is a flow chart of the overall HAB encryption operation step, after checking this figure, then we will follow it step by step.     Fig 2. MXRT1050 HAB encrypted image flow chart     The app image we used in this article is the RAM app, so, at first, we need to prepare one RAM based app image. In this document, we are directly use the prepared  RAM based app image: evkbimxrt1050_led_softwarereset_0xa000.s19, this app code function is: After download the code to the MIMXRT1050-EVKB(qspi flash) board, the on board led D18 will blinky and printf the information, after pressing the WAKEUP button SW8, the code will implement software reset and printf the related information. The unsigned code test print result are as follows:      BOARD RESET start.  Helloworld. WAKEUP key pressed, will do software system reset.    BOARD RESET start.  Helloworld. 2.1 CST tool preparation      Because the contains a lot of steps, then customer can refer to the following document do the related configuration, this document, we won’t give the CST configuration detail steps. Please check these documents: https://www.cnblogs.com/henjay724/p/10219459.html https://community.nxp.com/docs/DOC-340904 Security Application Note AN12079 After the CST tool configuration, please copy the cst.exe, crts folder, key folder from cst folder to the same folder that holds elftosb executable files: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\elftosb\win Please also copy SRK_1_2_3_4_fuse.bin and SRK_1_2_3_4_table.bin to the above folder. 2.2  Sign flashloader    Please refer to application note AN12079 chapter 3.3.1, copy flashloader.elf from folder path: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Flashloader And the imx-flexspinor-normal-signed.bd  from folder path: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\bd_file\imx10xx to the folder: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\elftosb\win Please open commander window under the elftosb folder, then input this commander: elftosb.exe -f imx -V -c imx-flexspinor-flashloader-signed.bd -o ivt_flashloader_signed.bin flashloader.elf   Fig 3.  Sign flashloader  This steps will generate the  ivt_flashlaoder_signed.bin, which is needed to put under the MFGtool OS Firmware folder, just used for enter the signed flashloader mode. 2.3 SRK and HAB mode fuse modification files Please refer to AN12079 chapter 4.3, copy the enable_hab.bd file from folder path: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\bd_file\imx10xx to this folder path: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\elftosb\win Please refer to the chapter 2.1 generated SRK_1_2_3_4_fuse.bin, modify the enable_hab.bd like the following picture: Fig 4. enable_hab.bd SRK and HAB mode fuse modification Then,  in the elftosb window, please input the following command, just used to generate the enable_hab.sb program file: elftosb.exe -f kinetis -V -c enable_hab.bd -o enable_hab.sb   Fig 5. SRK and HAB mode program files generation 2.4 APP Encrypted Image      If you want to do the HAB encrypted image download, you need to prepare one non-XIP app image, here we prepared one RAM based APP srec files.      Because the app file is the RAM files, then we also need the related RAM encrypted .bd files, please copy imx-itcm-encrypted.bd from the folder path:      Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\bd_file\imx10xx to this folder path: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\elftosb\win Open imx-itcm-encrypted.bd, then modify the following content: options {     flags = 0x0c;     # Note: This is an example address, it can be any non-zero address in ITCM region     startAddress = 0x8000;     ivtOffset = 0x1000;     initialLoadSize = 0x2000;     # Note: This is required if the cst and elftsb are not in the same folder     # Note: This is required if the default entrypoint is not the Reset_Handler     #       Please set the entryPointAddress to Reset_Handler address   entryPointAddress = 0x0000a2dd; } Here, we need to note these two points: (1)    ivtOffset = 0x1000; If the external flash is flexspi flash, then we need to modify ivtOffset as 0X1000, if it is the nandflash, we need to use the 0X400. (2) entryPointAddress = 0x0000a2dd; The entryPointsAddress should be the app code reset handlder, it is the app start address+4 data, the entry address is also OK, but we suggest you to use the app Reset_Handler address. Fig 6. App reset handler address Then input the following commander in the elftosb windows: elftosb.exe -f imx -V -c imx-itcm-encrypted.bd -o ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted.bin evkbimxrt1050_led_softwarereset_0xa000.s19 Fig 7. App HAB Encrypted file generation Please note, we need to record the generated key blob offset address, it is 0XA00, just like the above data in the red frame, this address will be used in the next chapter’s .bd file. After this step, it will generate 7 files:          (1)  ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted.bin, this file includes the FDCB which is filled with 0, IVT, BD, DCD, APP HAB encrypted image data, CSF data (2)  ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted_nopadding.bin, compare with ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted.bin, this file deletes the 0s which is above IVT range. (3)  Csf.bin, it is the HAB data area, you can find the data contains the csf data, it is from 0X8000 to 0X8F80 in the generated ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted.bin. Fig 8. Csf data and the encrypted app relationship      (4) dek.bin Fig 9. Dek data DEK data is the AES-128 bits key, it is not defined by the customer, it is random generated automatically by the HAB encrypted tool. (5) input.csf Open it, you can find the following content: Fig10. Input csf file content (6) rawbytes.bin,  this is the app image plaintext data, it doesn’t contains the FDCB,IVT,BOOTDATA, DCD, csf etc.    (7) temp.bin, it is the temporary file, compare with ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted.bin, no csf files.   2.5 HAB Encrypted QSPI program file    Here we need to prepare one program_flexspinor_image_qspinor_keyblob.bd file, and put it under the same folder as elftosb, this file is used to generate the HAB encrypted program .sb file. Because the flashloader package didn’t contains it, then we paste all the related content, and I will also attach it in the attachment. # The source block assign file name to identifiers sources { myBinFile = extern (0); dekFile = extern (1); } constants { kAbsAddr_Start= 0x60000000; kAbsAddr_Ivt = 0x60001000; kAbsAddr_App = 0x60002000; } # The section block specifies the sequence of boot commands to be written to the SB file section (0) { #1. Prepare Flash option # 0xc0000006 is the tag for Serial NOR parameter selection # bit [31:28] Tag fixed to 0x0C # bit [27:24] Option size fixed to 0 # bit [23:20] Flash type option # 0 - QuadSPI SDR NOR # 1 - QUadSPI DDR NOR # 2 - HyperFLASH 1V8 # 3 - HyperFLASH 3V # 4 - Macronix Octal DDR # 6 - Micron Octal DDR # 8 - Adesto EcoXIP DDR # bit [19:16] Query pads (Pads used for query Flash Parameters) # 0 - 1 # 2 - 4 # 3 - 8 # bit [15:12] CMD pads (Pads used for query Flash Parameters) # 0 - 1 # 2 - 4 # 3 - 8 # bit [11: 08] Quad Mode Entry Setting # 0 - Not Configured, apply to devices: # - With Quad Mode enabled by default or # - Compliant with JESD216A/B or later revision # 1 - Set bit 6 in Status Register 1 # 2 - Set bit 1 in Status Register 2 # 3 - Set bit 7 in Status Register 2 # 4 - Set bit 1 in Status Register 2 by 0x31 command # bit [07: 04] Misc. control field # 3 - Data Order swapped, used for Macronix OctaFLASH devcies only (except MX25UM51345G) # 4 - Second QSPI NOR Pinmux # bit [03: 00] Flash Frequency, device specific load 0xc0000006 > 0x2000; # Configure QSPI NOR FLASH using option a address 0x2000 enable flexspinor 0x2000; #2 Erase flash as needed. erase 0x60000000..0x60020000; #3. Program config block # 0xf000000f is the tag to notify Flashloader to program FlexSPI NOR config block to the start of device load 0xf000000f > 0x3000; # Notify Flashloader to response the option at address 0x3000 enable flexspinor 0x3000; #5. Program image load myBinFile > kAbsAddr_Ivt; #6. Generate KeyBlob and program it to flexspinor # Load DEK to RAM load dekFile > 0x10100; # Construct KeyBlob Option #--------------------------------------------------------------------------- # bit [31:28] tag, fixed to 0x0b # bit [27:24] type, 0 - Update KeyBlob context, 1 Program Keyblob to flexspinor # bit [23:20] keyblob option block size, must equal to 3 if type =0, # reserved if type = 1 # bit [19:08] Reserved # bit [07:04] DEK size, 0-128bit 1-192bit 2-256 bit, only applicable if type=0 # bit [03:00] Firmware Index, only applicable if type = 1 # if type = 0, next words indicate the address that holds dek # the 3rd word #---------------------------------------------------------------------------- # tag = 0x0b, type=0, block size=3, DEK size=128bit load 0xb0300000 > 0x10200; # dek address = 0x10100 load 0x00010100 > 0x10204; # keyblob offset in boot image # Note: this is only an example bd file, the value must be replaced with actual # value in users project load 0x0000a000 > 0x10208; enable flexspinor 0x10200; #7. Program KeyBlob to firmware0 region load 0xb1000000 > 0x10300; enable flexspinor 0x10300; }‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ Please note, in the above chapter, fig 7, we mentioned the keyblob offset address, we need to modify it in the following code:     load 0x0000a000 > 0x10208; Now, combine program_flexspinor_image_qspinor_keyblob.bd, ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted_nopadding.bin and dek.bin file together, we use the following commander to generate the boot_image.sb: elftosb.exe -f kinetis -V -c program_flexspinor_image_qspinor_keyblob.bd -o boot_image.sb ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted_nopadding.bin dek.bin Fig 11. App HAB encrypted program file generation Until now, we will find, all the related HAB encrypted files is prepared. 2.6 MFG Tool program HAB Encrypted files to RT1050-EVKB        Before we program it, please copy the following 3 files which is in the elftosb folder: ivt_flashloader_signed.bin enable_hab.sb boot_image.sb to this folder: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\mfgtools-rel\Profiles\MXRT105X\OS Firmware Please modify cfg.ini, the file path is: Flashloader_i.MXRT1050_GA\Flashloader_RT1050_1.1\Tools\mfgtools-rel Modify the content as: [profiles] chip = MXRT105X [platform] board = [LIST] name = MXRT105X-SecureBoot Choose MXRT105X-SecureBoot program mode. Then open the tool MfgTool2.exe, the board MIMXRT1050-EVKB(need to modify the on board resistor, use the qspi flash) mode should be serial download mode, just modify SW7:1-OFF,2-OFF,3-OFF, 4-ON, connect two usb cable between PC and the board J28 and J9. After the connection, you will find the MfgTool2.exe can detect the HID device: Fig 12. MFG tool program After the program is finished, power off the board, modify the boot mode to internal boot, it is SW7:1-OFF,2-OFF,3-ON, 4-OFF,connect the COM terminal, power on the EVKB board, after reset, you will find the D18 led is blinking, after you press the SW8, you will find the following printf information: BOARD RESET start. Helloworld. WAKEUP key pressed, will do software system reset. ? BOARD RESET start. Helloworld.‍‍‍‍‍‍‍‍‍‍‍‍‍ So, the HAB encrypted image works OK now. 3. App HAB encrypted image structure analysis 3.1 MCUBootUtility Configuration to check the RT Encrypted image      Here, we can also use  MCUBootUtility tool to check the RT chip encrypted image and the fuse data.      If the cst is your own configured, please do the following configuration at first:     (1)Copy the configured cst folder to folder: NXP-MCUBootUtility-2.0.0\tools Delete the original cst folder. (2)Copy SRK_1_2_3_4_fuse.bin and SRK_1_2_3_4_table.bin to folder:  NXP-MCUBootUtility-2.0.0\gen\hab_cert Now, you can use the new MCUBootutility to connect your board which already done the HAB encrypted method. 3.1 RT1050 fuse map comparation Before do the HAB encrypted image program, I have read out the whole fuse map as follows: Fig 13. MIMXRT1050-EVKB fuse map before HAB encrypted image Fig 14. MIMXRT1050-EVKB fuse map after HAB encrypted image Compare the fuse map between do the HAB encrypted image and no HAB encrypted image, we can find two difference: HAB mode, 0X460 bit1:0 open, 1 close SRK area We can find, after program the HAB encrypted image, the SRK fuse data is the same as the SRK data which is defined in the enable_hab.bd. 3.2  Readout HAB encrypted QSPI APP image structure analysis From MCUBootUtility tool, we can find the HAB Encypted image structure should be like this: Fig 15. HAB Encrypted image structure What about the real example image case? Now, we use the MCUbootUtility tool to read out our HAB encrypted image, from address 0X60000000, the readout size is 0XB000. The detail image structure is like following:   Fig 16. HAB Encypted image example structure   1): IVT:  hdr,  IVT header, more details, check hab_hdr 2):    IVT: entry, the app entrypointAddress, it should be the reset_handler address, in this document example, it is the address 0xa004 data, the plaintext is 0X00A2DD, but after the HAB encrypted, we can find the address -x60002004 data is the encrypted data 3):  IVT: reserved 4):  IVT: DCD, it is used for the DRAM SEMC configuration, in this example, we didn’t use the SDDRAM, so the data is 0. 5):  IVT: BOOT_DATA, used to indicate the BOOT_DATA  RAM start address 0X9020. 6):  IVT: self, ivt self RAM start address is 0X9000 7):  IVT:CSF, it is used to indicate the CST start address, this example csf ram address is 0X00010000. 8):  IVT:reserved 9): BOOT_DATA:  RAM image start,  the whole image RAM start address, this RAM example BOOT_DATA is 0X8000,0XA000-0X2000=0X8000 10): BOOT_DATA: size, APP file size, it is 0X0000A200, after checking the file generated HAB encrypted app image size, you can find the image end size is really 0XA200, just like the fig 16. 11):  HAB  Encypted app data,  please check ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted.bin file, the address 0X2000-0X7250 data, you will find it is the same.   12): HAB data, it incluses the csf, certificate etc data, you can compare the file ivt_evkbimxrt1050_led_softwarereset_0xa000_encrypted.bin address 0X8000-0x8f70 data, it is the same. 13):DEK blob, it is the DEK key blob related data, the offset address is 0XA000, the same as fig 7. FDCB,IVT,BOOT DATA are all plaintext, but app image area is the HAB encrypted data, HAB and the DEK blob is the generated data put in the related memory. Conclusion     This document we mainly use the elftosb and the MFGTool to generate the HAB encrypted image, and download it to the RT1050 EVKB board, document give the whole detail steps, and us ethe MCUBootutility tool to read out the HAB encrypted image, and analysis the HAB encrypted image structure with the examples.  After compare with the generated mid files, we can find all the data is consist, and all the encrypted data range is the same. The test result also demonstrate the HAB encrypted code function works, the HAB encrypted boot has no problems. All the related files is in the attachment.      
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i.MX RT1050 is the first set of processors in NXP's crossover processor family, combining the high-performance and high level of integration on an applications processors with the ease of use and real-time functionality of a microcontroller. As the first device in a new family, we have had some learning and improvements that have come along the way. There have been some changes and improvements to the processor and also our enablement for the device. This can result in some revisions of hardware and software not being directly compatible with each other out of the box. In particular, some software that has been released for the A0 silicon revision (found on EVK boards) doesn't run on the A1 silicon revision (EVKB boards). In order to minimize the risk of compatibility issues, we recommend that all customers move to SDK 2.3.1 or higher. The SDK 2.3.1 is listed as supporting the EVKB hardware specifically, but the SDK is compatible with the EVK (non-B) hardware. We also recommend that customers using the DAPLink firmware for the OpenSDA debugging circuit built into the EVK/EVKB update to the latest version available on the www.nxp.com/opensda site. The flashloader package has also been updated. Rev 1.1 or later should be used (Flashloader i.MX-RT1050). There are many application notes available for RT1050. Many of these application notes were written based on the original silicon revision and early releases of enablement software. We are in the process of reviewing the published application notes and application note software to prioritize updating them where needed based on the latest enablement and recommendations. If you are in a situation where you need to use SDK 2.3.0 on A1 silicon, the most likely problem area involves some new clock gate bits that were added on the A1 silicon revision. These bits weren't present on the A0 silicon, so SDK 2.3.0 will clear them which disables external memory interfaces. If you comment out  the call to BOARD_BootClockGate() that is in the BOARD_BootClockRUN function (found in the clock_config.c file), that should allow the SDK 2.3.0 software to run on an A1 silicon/EVKB. For more information: MCUXpresso SDK RT1050 migration app note  i.MX RT1050 CMSIS-DAP drag-and-drop programming 
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i.MXRT1050 MCU supports 10M/100M Ethernet MAC. Nowadays, LAN8720A is a very common PHY used in many networking design. In this document, I will show you how to use LAN8720A with i.MXRT1050.  1. Schematic   In this design example,  ENET_RST  is connected to GPIO_AD_B1_04      ENET_INT is connected to GPIO_AD_B0_15      2. Source code modification In the i.MXRT1050 SDK, the source code files of the PHY are fsl_phy.c and fsl_phy.h. The registers of LAN8720A need to be added into the source code. Below is the registers of LAN8720A. The details can be found in the LAN8720A datasheet. ( The modified fsl_phy.c and fsl_phy.h are attached)   In the pinmux.c, modify the GPIO Mux setting of the ENET_INT and ENET_RST.   IOMUXC_SetPinMux(IOMUXC_GPIO_AD_B1_04_GPIO1_IO20, 0U);                                      IOMUXC_SetPinMux(IOMUXC_GPIO_AD_B0_15_GPIO1_IO15, 0U);                                      IOMUXC_SetPinConfig(IOMUXC_GPIO_AD_B1_04_GPIO1_IO20, 0xB0A9u);                                  IOMUXC_SetPinConfig(IOMUXC_GPIO_AD_B0_15_GPIO1_IO15, 0xB0A9u);                               This is the part of the source code to reset the PHY in the main() function. gpio_pin_config_t gpio_config = {kGPIO_DigitalOutput, 0, kGPIO_NoIntmode}; GPIO_PinInit(GPIO1, 20, &gpio_config); GPIO_PinInit(GPIO1, 15, &gpio_config); GPIO_WritePinOutput(GPIO1, 15, 1); GPIO_WritePinOutput(GPIO1, 20, 0); delay(); GPIO_WritePinOutput(GPIO1, 20, 1); For more example codes, please refer to the demo_apps/lwip in the i.MXRT SDK package. Reference: i.MXRT1050 web page : i.MX RT1050 MCU/Applications Crossover Processor | Arm® Cortex®-M7 @600 MHz, 512KB SRAM |NXP  MCUXpresso SDK web page : MCUXpresso SDK|NXP 
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The path of SDRAM Clock in Clock Tree                 According CCM clock tree in i.MXRT1050 reference manual, we can abstract part of SDRAM clock, and draw it’s diagram below.   Descriptions for Diagram 1 (1) PLL2 PFD2                 ① Registers related to PLL2 PFD2 ---CCM_ANALOG_PLL_SYSn (page 767, in reference manual) Address: 0x400D_8030h important bits: bit[15:14]---- select clock source. Bit[13] ----- Enable PLL output Bit[0]------- This field controls the PLL loop divider. 0 - Fout=Fref*20; 1 - Fout=Fref*22. ---CCM_ANALOG_PLL_SYS_NUM(page 768, in reference manual) Address: 0x400D_8050h important bits: bit[29:0]--- 30 bit numerator (A) of fractional loop divider (signed integer) ---CCM_ANALOG_PLL_SYS_DENOM (page 769, in reference manual) Address: 0x400D_8060h important bits: bit[29:0]---- 30 bit Denominator (B) of fractional loop divider (unsigned integer).   ---CCM_ANALOG_PFD_528n (page 769, in reference manual) Address: 0x400D_8100h important bits: bit[21:16]----- This field controls the fractional divide value. The resulting frequency shall be 528*18/PFD2_FRAC where PFD2_FRAC is in the range 12-35.   ② Computational formula PLL2_PFD2_OUT=(External 24MHz)*(Fout + A/B) * 18/ PFD2_FRAC   ③ Example for PLL2_PFD2_OUT computation CCM_ANALOG_PLL_SYSn[0] = 1  // Fout=Fref*22 CCM_ANALOG_PLL_SYS_NUM[29:0] = 56  // A = 56 CCM_ANALOG_PLL_SYS_DENOM[29:0] = 256  // B=256 CCM_ANALOG_PFD_528n[21:16] = 29                       // PFD2_FRAC=29   PLL2_PFD2_OUT = 24 * (22 + 56/256)*18/29 = 331MHz (330.98MHz)   (2) Clock Select Register : CCM_CBCDR Address: 0x 400F_C014h important bits: SEMC_ALT_CLK_SEL & SEMC_CLK_SEL & SEMC_PODF bit[7] --- bit[SEMC_ALT_CLK_SEL] 0---PLL2 PFD2 will be selected as alternative clock for SEMC root clock 1---PLL3 PFD1 will be selected as alternative clock for SEMC root clock Bit[6] --- bit[SEMC_CLK_SEL] 0----Periph_clk output will be used as SEMC clock root 1----SEMC alternative clock will be used as SEMC clock root Bit[18:16] --- bit[SEMC_PODF] Post divider for SEMC clock. NOTE: Any change of this divider might involve handshake with EMI. See CDHIPR register for the handshake busy bits. 000 divide by 1 001 divide by 2 010 divide by 3 011 divide by 4 100 divide by 5 101 divide by 6 110 divide by 7 111 divide by 8 Example for configuration of SDRAM Clock   Example : 166MHz SDRAM Clock   ---- 0x400D8030 = 0x00002001 // wirte  0x00002001 to CCM_ANALOG_PLL_SYSn ---- 0x400D8050 = 0x00000038 // write 0x00000038 to CCM_ANALOG_PLL_SYS_NUM ---- 0x400D8060 = 0x00000100 // write 0x00000100 to CCM_ANALOG_PLL_SYS_DENOM ---- 0x400D8100 = 0x001d0000 // write 0x001d0000 to CCM_ANALOG_PFD_528n ---- 0x400FC014 = 0x00010D40 // write 0x00010D40 to CCM_CBCDR, divided by 2         NXP TIC team Weidong Sun 2018-06-01
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In the SDK_2.7.0_EVKB-IMXRT1050, it contains some eIQ machine learning demo projects, there's the tensorflow_lite_kws among them. It's a keyword spotting example that is based on Keyword spotting for Microcontrollers and it deploys a deepwise separable convolutional neural network called MobileNet in this demo project. It can classify a one-second audio clip as either silence, an unknown word, "yes", "no", "up", "down", "left", "right", "on", "off", "stop", or "go". Figure 1 shows the components that comprise it. Fig 1 Training Our New Model The model we are using is trained with the TensorFlow script which is designed to demonstrate how to build and train a model for audio recognition using TensorFlow. The script makes it very easy to train an audio recognition model. Among other things, it allows us to do the following: Download a dataset with audio featuring 20 spoken words. Choose which subset of words to train the model on. Specify what type of preprocessing to use on the audio. Choose from several different types of the model architecture. Optimize the model for microcontrollers using quantization. When we run the script, it downloads the dataset, trains a model, and outputs a file representing the trained model. We then use some other tools to convert this file into the correct form for TensorFlow Lite. Training in virtual machine (VM) Preparation Make sure the TensorFlow has been installed, and since the script downloads over 2GB of training data, it'll need a good internet connection and enough free space on the machine. Note that: The training process itself can take several hours, be patient. Training To begin the training process, use the following commands to clone ML-KWS-for-MCU. git clone https://github.com/ARM-software/ML-KWS-for-MCU.git‍‍‍‍‍‍ The training scripts are configured via a bunch of command-line flags that control everything from the model’s architecture to the words it will be trained to classify. The following command runs the script that begins training. You can see that it has a lot of command-line arguments: python ML-KWS-for-MCU/train.py --model_architecture ds_cnn --model_size_info 5 64 10 4 2 2 64 3 3 1 1 64 3 3 1 1 64 3 3 1 1 64 3 3 1 1 \ --wanted_words=zero, one, two, three, four, five, six, seven, eight, nine \ --dct_coefficient_count 10 --window_size_ms 40 \ --window_stride_ms 20 --learning_rate 0.0005,0.0001,0.00002 \ --how_many_training_steps 10000,10000,10000 \ --data_dir=./speech_dataset --summaries_dir ./retrain_logs --train_dir ./speech_commands_train ‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ Some of these, like --wanted_words=zero, one, two, three, four, five, six, seven, eight, nine. By default, the selected words are yes, no, up, down, left, right, on, off, stop, go, but we can provide any combination of the following words, all of which appear in our dataset: Common commands: yes, no, up, down, left, right, on, off, stop, go, backward, forward, follow, learn Digits zero through nine: zero, one, two, three, four, five, six, seven, eight, nine Random words: bed, bird, cat, dog, happy, house, Marvin, Sheila, tree, wow Others set up the output of the script, such as --train_dir=/content/speech_commands_train, which defines where the trained model will be saved. Leave the arguments as they are, and run it. The script will start off by downloading the Speech Commands dataset (Figure 2), which consists of over 105,000 WAVE audio files of people saying thirty different words. This data was collected by Google and released under a CC BY license, and you can help improve it by contributing five minutes of your own voice. The archive is over 2GB, so this part may take a while, but you should see progress logs, and once it's been downloaded once you won't need to do this step again. You can find more information about this dataset in this Speech Commands paper. Fig 2 Once the downloading has completed, some more output will appear. There might be some warnings, which you can ignore as long as the command continues running. Later, you'll see logging information that looks like this (Figure 3). Fig 3 This shows that the initialization process is done and the training loop has begun. You'll see that it outputs information for every training step. Here's a break down of what it means: Step shows that we're on the step of the training loop. In this case, there are going to be 30,000 steps in total, so you can look at the step number to get an idea of how close it is to finishing. rate is the learning rate that's controlling the speed of the network's weight updates. Early on this is a comparatively high number (0.0005), but for later training cycles it will be reduced 5x, to 0.0001, then to 0.00002 at last. accuracy is how many classes were correctly predicted on this training step. This value will often fluctuate a lot, but should increase on average as training progresses. The model outputs an array of numbers, one for each label, and each number is the predicted likelihood of the input being that class. The predicted label is picked by choosing the entry with the highest score. The scores are always between zero and one, with higher values representing more confidence in the result. cross-entropy is the result of the loss function that we're using to guide the training process. This is a score that's obtained by comparing the vector of scores from the current training run to the correct labels, and this should trend downwards during training. checkpoint After a hundred steps, you should see a line like this: This is saving out the current trained weights to a checkpoint file (Figure 4). If your training script gets interrupted, you can look for the last saved checkpoint and then restart the script with --start_checkpoint=/tmp/speech_commands_train/best/ds_cnn_xxxx.ckpt-400 as a command line argument to start from that point . Fig 4 Confusion Matrix After four hundred steps, this information will be logged: The first section is a confusion matrix. To understand what it means, you first need to know the labels being used, which in this case are "silence", "unknown", "zero", "one", "two", "three", "four", "five", "six", "seven", "eight", and "nine". Each column represents a set of samples that were predicted to be each label, so the first column represents all the clips that were predicted to be silence, the second all those that were predicted to be unknown words, the third "zero", and so on. Each row represents clips by their correct, ground truth labels. The first row is all the clips that were silence, the second clips that were unknown words, the third "zero", etc. This matrix can be more useful than just a single accuracy score because it gives a good summary of what mistakes the network is making. In this example you can see that all of the entries in the first row are zero (Figure 5), apart from the initial one. Because the first row is all the clips that are actually silence, this means that none of them were mistakenly labeled as words, so we have no false negatives for silence. This shows the network is already getting pretty good at distinguishing silence from words. If we look down the first column though, we see a lot of non-zero values. The column represents all the clips that were predicted to be silence, so positive numbers outside of the first cell are errors. This means that some clips of real spoken words are actually being predicted to be silence, so we do have quite a few false positives. A perfect model would produce a confusion matrix where all of the entries were zero apart from a diagonal line through the center. Spotting deviations from that pattern can help you figure out how the model is most easily confused, and once you've identified the problems you can address them by adding more data or cleaning up categories.                                                            Fig 5                                                             Validation After the confusion matrix, you should see a line like Figure 5 shows. It's good practice to separate your data set into three categories. The largest (in this case roughly 80% of the data) is used for training the network, a smaller set (10% here, known as "validation") is reserved for evaluation of the accuracy during training, and another set (the last 10%, "testing") is used to evaluate the accuracy once after the training is complete. The reason for this split is that there's always a danger that networks will start memorizing their inputs during training. By keeping the validation set separate, you can ensure that the model works with data it's never seen before. The testing set is an additional safeguard to make sure that you haven't just been tweaking your model in a way that happens to work for both the training and validation sets, but not a broader range of inputs. The training script automatically separates the data set into these three categories, and the logging line above shows the accuracy of model when run on the validation set. Ideally, this should stick fairly close to the training accuracy. If the training accuracy increases but the validation doesn't, that's a sign that overfitting is occurring, and your model is only learning things about the training clips, not broader patterns that generalize Training Finished In general, training is the process of iteratively tweaking a model’s weights and biases until it produces useful predictions. The training script writes these weights and biases to checkpoint files (Figure 6). Fig 6 A TensorFlow model consists of two main things: The weights and biases resulting from training A graph of operations that combine the model’s input with these weights and biases to produce the model’s output At this juncture, our model’s operations are defined in the Python scripts, and its trained weights and biases are in the most recent checkpoint file. We need to unite the two into a single model file with a specific format, which we can use to run inference. The process of creating this model file is called freezing—we’re creating a static representation of the graph with the weights frozen into it. To freeze our model, we run a script that is called as follows: python ML-KWS-for-MCU/freeze.py --model_architecture ds_cnn --model_size_info 5 64 10 4 2 2 64 3 3 1 1 64 3 3 1 1 64 3 3 1 1 64 3 3 1 1 \ --wanted_words=zero, one, two, three, four, five, six, seven, eight, nine \ --dct_coefficient_count 10 --window_size_ms 40 \ --window_stride_ms 20 --checkpoint ./speech_commands_train/best/ds_cnn_9490.ckpt-21600 \ --output_file=./ds_cnn.pb‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ To point the script toward the correct graph of operations to freeze, we pass some of the same arguments we used in training. We also pass a path to the final checkpoint file, which is the one whose filename ends with the total number of training steps. The frozen graph will be output to a file named ds_cnn.pb. This file is the fully trained TensorFlow model. It can be loaded by TensorFlow and used to run inference. That’s great, but it’s still in the format used by regular TensorFlow, not TensorFlow Lite. Convert to TensorFlow Lite Conversion is a easy step: we just need to run a single command. Now that we have a frozen graph file to work with, we’ll be using toco, the command-line interface for the TensorFlow Lite converter. toco --graph_def_file=./ds_cnn.pb --output_file=./ds_cnn.tflite \ --input_shapes=1,49,10,1 --input_arrays=Reshape_1 --output_arrays='labels_softmax' \ --inference_type=QUANTIZED_UINT8 --mean_values=227 --std_dev_values=1 \ --change_concat_input_ranges=false \ --default_ranges_min=-6 --default_ranges_max =6‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ In the arguments, we specify the model that we want to convert, the output location for the TensorFlow Lite model file, and some other values that depend on the model architecture. we also provide some arguments (inference_type, mean_values, and std_dev_values) that instruct the converter how to map its low-precision values into real numbers. The converted model will be written to ds_cnn.tflite, this a fully formed TensorFlow Lite model! Create a C array We’ll use the xxd command to convert a TensorFlow Lite model into a C array in the following. xxd -i ./ds_cnn.tflite > ./ds_cnn.h cat ./ds_cnn.h‍‍‍‍‍‍‍‍ The final part of the output is the file’s contents, which are a C array and an integer holding its length, as follows: Fig 7 Next, we’ll integrate this newly trained model with the tensorflow_lite_kws project. Using the Model in tensorflow_lite_kws Project To use the new model, we need to do two things: In source/ds_cnn_s_model.h, replace the original model data with our new model. Update the label names in source/kws.cpp with our new ''zero'', ''one'', ''two'', ''three'', ''four'', ''five'', ''six'', ''seven'', ''eight'' and ''nine'' labels. const std::string labels[] = {"Silence", "Unknown","zero", "one", "two", "three","four", "five", "six", "seven","eight", "nine"};‍‍‍ Before running the model in the EVKB-IMXRT1050 board (Figure 8), please refer to the readme.txt to do the preparation, in further, the file also demonstrates the steps of testing, please follow them. Fig 8 Figure 9 shows the testing I did, I've attached the model file, please give a try by yourself. Fig 9
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How to create RT AVB switch&endpoint platform 1. Abstract In the previous article, it talked about how to use a single-point RT1170 as a talker and a single-point RT1170 as a listener, and connect the two boards directly to implement AVB endpoint testing. However, in actual use, many applications are multipoint to multipoint, but AVB switch is required. Therefore, based on the previous article, this article adds another listener endpoint and AVB switch to implement an AVB platform with one talker and two listeners. Fig 1 The AVB switch can be a third-party AVB switch product. Of course, you can also consider using NXP's upcoming new product RT1180. This chip has AVB/TSN switch function, and our RT1180 supporting stack has also been released. 2. Platform creation This article will use two AVB switches to do AVB testing: one uses the NXP official MIMXRT1180-EVK as an AVB switch, and the other uses the third-party product MOTU's AVB switch. The endpoints use three NXP MIMXRT1170-EVK boards, one for talker configuration and the other two for listener configuration. For the configuration of RT1170 as endpoint, that is, talker and listener, you can refer to the previous article: RT1170 AVB fresh tasting Here you can directly start quickly, take the avb_app.bin prepared in the stack and burn it directly to MIMXRT1170-EVK for talker and listener configuration. Of course, if there are some customized functions that modify the source code, you can also refer to the above article to recompile, generate the avb_app.bin file and then burn it. 2.1 Software and hardware Hardware:       MOTU AVB SWITCH(switch)       MIMXRT1180-EVK*1(switch)       MIMXRT1170-EVK*3(1: talker, 2: listener), hardware need to be modified, refer to the previous document Software: RT1170 AVB/TSN stack: genavb_tsn-mcuxpresso-SDK_2_13_0-5_6_1: https://mcuxpresso.nxp.com/download/52643189c4d74a7b26b8e096ab28df0e RT1180 AVB/TSN stack: genavb_tsn-mcuxpresso-SDK_2_15_0-6_0_0 : https://mcuxpresso.nxp.com/download/c584c33a8d4f55c29b5505b9be8f537a   2.2 Configure RT1170 AVB endpoints Directly burn the files in avbstack: genavb_tsn-mcuxpresso-SDK_2_13_0-5_6_1\binaries\genavb-avb_audio_app-evaluation-freertos_rt1176-5_6_1.tar\genavb-avb_audio_app-evaluation-freertos_rt1176-5_6_1\release\avb_app.bin to the three MIMXRT1170-EVK development boards and enter the serial download mode to program: Fig 2 The three boards are burned with the same code. After burning, let the board enter the internal boot mode and configure the talker and listener through the serial port. After the code is burned successfully, the onboard serial port will keep sending log information. You only need to enter INSERT on the keyboard to enter the shell command line state. 2.2.1 1MIMXRT1170-EVK do the talker configuration cd .. ls mkdir avb_app write avb_app/mclock_role 0 mkdir avdecc write avdecc/btb_mode 0 mkdir fgptp write fgptp/gmCapable 1 mkdir port0 write port0/hw_addr 00:22:33:44:55:66 2.2.2 2 MIMXRT1170-EVK do the listener configuration cd .. ls mkdir avb_app write avb_app/mclock_role 1 mkdir avdecc write avdecc/btb_mode 1 write avdecc/talker_id 0x00049f4455660000 2.3 AVB Switch configuration     The following are two SWITCH configuration connections: 2.3.1 MOTU AVB Switch Use MOTU AVB switch as the AVB switch connection block diagram: Fig 3   The physical board connections are as follows: Fig 4 For the dedicated AVB switch, no specific configuration is required, because you can think of it as a switch with AVB function, which can realize the forwarding function of AVB data. You only need to connect the 1G network port of a talker and the 1G network ports of two listeners to the network port of MOTU AVB SWITCH. Then as long as the functions of the talker and the listener are normal, the entire audio transmission can be normal. The talker is responsible for collecting the audio data information of the microphone and then forwarding it to the two listeners for playback. Of course, the two listeners need to be connected to the speakers respectively. 2.3.2 RT1180 AVB switch For the configuration of RT1180 AVB switch, there are two methods: quick start and self-compilation. If there is no change in the source code, you can directly use the bin file that comes with the stack. Here you need to pay attention to select the correct bin file. RT1180 has two cores: CM33 and CM7 cores. The CM33 image supports the TSN/AVB bridge function, that is, the switch, and the CM7 image supports the TSN endpoint function.    MIMXRT1180-EVK contains multi-network ports, the situation is: Fig 5 Fig 6 Therefore, when using the AVB switch network port, you need to pay attention to using ENET0, 1, 2, and 3 ports. The connection diagram of using MIMXRT1180-EVK as the AVB switch network port is as follows: Fig 7 The actual connection diagram is as follows: Fig 8 To implement the RT1180 code, you need to download the RT1180 M33 TSN bridge code to the MIMXRT1180-EVK board. If the source code of the AVB/TSN stack does not need to be modified, you can use the ready-made bin file for testing: genavb_tsn-mcuxpresso-SDK_2_15_0-6_0_0\binaries\genavb-tsn_app-evaluation-freertos_rt1189_cm33-6_0_0\release\tsn_app.bin There are many ways to burn, you can use tools or command line methods. The tool can be MCUBootutility or the official SEC tool. Here we choose to use the MCUBootutility tool, download link: https://github.com/JayHeng/NXP-MCUBootUtility/releases/tag/v6.2.0 If you use the SEC tool to download, you can refer to the stack documentation: genavb_tsn-mcuxpresso-SDK_2_15_0-6_0_0\doc\ NXP_GenAVB_TSN_MCUXpresso_User_s_Guide_6_0_rev0.pdf, chapter 11 Flash Image booting. When use the MCUBootutility tool, it needs to do the modification: \NXP-MCUBootUtility-6.2.0\src\targets\MIMXRT1189 \MIMXRT1189\bltargetconfig.py Modify: #flexspiNorMemBase0 = 0x38000000 # CM33 Secure #flexspiNorMemBase0Ns = 0x28000000 # CM33 Non-Secure To: flexspiNorMemBase0 = 0x28000000 # CM33 Non-Secure flexspiNorMemBase0Ns = 0x38000000 # CM33 Secure Fig 9 Burn the tsn_app.bin to the RT1180 address 0x2800b000。 Let the MIMXRT1180-EVK board enter serial download mode,SW5:1-OFF,2-OFF,3-OFF,4-ON. Then, find another usb cable to connect J33 to do the code flash downloading. After the code is programmed, need to enter the internal boot mode for QSPI: SW5:1-OFF,2-ON,3-OFF,4-OFF. This completes the burning of the app with AVB switch function. This code does not need to enter the shell to configure the filesystem like RT1170. For the RT1180 bridge code, after burning, the switch function will be built-in after restarting. Of course, if you need to recompile your own project, you can directly refer to the stack documentation: NXP_GenAVB_TSN_MCUXpresso_User_s_Guide_6_0_rev0.pdf. If you use Linux system to compile, the method is the same as RT1170, three steps:      (1) Patch the AVB stack for the RT1180 SDK     (2)add two soft links to the RT1180 AVB stack, one for the board SDK and the other for the AVB SDK source code. The structure is as follows:   Fig 10    (3) At last, build ./ build_release.sh \genavb_tsn-mcuxpresso-SDK_2_15_0-6_0_0\genavb-apps-freertos-6_0_0.tar\genavb-apps-freertos-6_0_0\boards\evkmimxrt1180\demo_apps\avb_tsn\tsn_app\cm33\armgcc\ build_release.sh Then, it will generate the according tsn_app.bin file. 3. AVB network data packet analysis I have always wanted to check the AVB network data packets, so I thought of the following method to do it. I also found a general network switch that can package some of the network ports to specific network ports. This method is used here just to check the basic packets. In principle, the general switch does not have the AVB physical layer function, so it should have some impact on the synchronization function. However, due to the limitation of the equipment, this article only has a basic understanding of the AVB data packet structure. Prepare a switch with port mirror function: NETGERA plus switch ProSAFE GS105E. Then configure the switch to mirror the data of ports 2 and 3 to port 1: Fig 11 Then the entire AVB system connection diagram is as follows: Fig 12 The physical connection diagram is as follows: Fig 13 Open the entire system platform and let the system function run, that is, the talker endpoint has sound input and the amplifiers of the two listener endpoints have output. Open the wireshark software on the PC and capture the packets. The captured situation is as follows: Fig 14 As you can see, there are many AVTP packets, and there are two destination addresses. To analyze AVTP packets, you must first know what the standard AVTP packets are like. The standard packets have the following structure: Fig 15 Next, open the wireshark software, configure the network port to be captured, and compare the captured data packets: Fig 16 As you can see, the whole packet is basically captured, but the details, such as VLAN tag and IEC 61883 header, are not present. This is probably caused by the physical layer of ordinary switches cannot support AVB. However, the audio data above can still be seen, and it is indeed dual-channel, but the data is only transmitted through one channel. Therefore, for the RT1170 listener, although a dual-channel speaker is connected, the two speakers correspond to the left and right channels, but when listening, only one speaker channel has sound, and the other has no sound. This is consistent with the captured data packet. The source of this is that the stack code uses one channel for microphone acquisition, and although the audio is configured with two channels, there is actually only one channel with data. So far, the architecture and test of the AVB switch&endpoint platform have been realized. The test effect can be viewed in the video.    
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1.  Abstract NXP EdgeReady solution can use RT106/5 S/L/A/F to achieve speech recognition, but the relevant support software libraries for the RT4-bit series are limited to the S/L/A/F series, if you want to use normal RT chips, how to achieve speech recognition functions? NXP officially launched the VIT software package in the SDK, which can support RT1060, RT1160, RT1170, RT600, RT500 to achieve SDK-based speech recognition functions. For the acquisition of weather information, usually customer can connect with a third-party platform or the cloud weather API, using http client method to access directly, the current weather API platforms, you can register it, then call the API directly, so you can use the RT SDK lwip socket client method to call the corresponding weather API, to achieve real-time specific geographical location weather forecast data.     This article will use MIMXRT1060-EVK to implement customer-defined wake-up word(WW) and voice recognition word recognition(VC) based on SDK VIT lib, and LWIP socket client to achieve real-time weather information acquisition in Shanghai, then print it to the terminal, this article mainly use the print to share the weather information, for the sound broadcasts, it also add the simple method to broadcast the fixed sound with mp3 audio data, but for the freely sound broadcast, it may need to use real-time TTS function, which is not added now.     The system block diagram of this document is as follows:   Fig 1 System Block diagram The VIT custom wake-up word of this system is "小恩小恩", and after waking up, one of the following recognition words can be recognized: ”开灯”("Turn on the lights"),“关灯”("Turn off the lights"),”今天天气”("Today's weather"),“明天天气”("Tomorrow's Weather"),“后天天气”("The day after tomorrow's weather"). Turn on the light or Turn off the lights , that is to control  the external LED red light on the EVK board. ”今天天气” gets today’s weather forecast, it is in the following format:                     "date": "2022-05-27",                     "week": "5",                     "dayweather": "阴",                     "nightweather": "阴",                     "daytemp": "28",                     "nighttemp": "21",                     "daywind": "东南",                     "nightwind": "东南",                     "daypower": "≤3",                     "nightpower": "≤3" “明天天气”,“后天天气” are the same format, but it is 1-2 days after the date of today. To get the weather data, the MIMXRT1060-EVK board needs to connect the network to achieve the acquisition of the Gaode Map(restapi.amap.com) Weather API data. 2.  Related preparations 2.1 Weather API Platform     At present, there are many third-party platforms that can obtain weather on the Internet for Chinese, such as: Baidu Intelligent Cloud, Baidu Map API, Huawei cloud platform, Juhe weather, Gaode Map API, and so on. This article tried several platform, the test results found: Baidu intelligent cloud, the number of daily free calls is small, the need for real-time synthesis of AK, SK, cumbersome to call; Baidu Map API needs to upload ID card information; Several others have a similar situation. In the end, the Gaode Map API with convenient registration, many daily calls and relatively full feedback weather data information was selected.     Here, we mainly talk about the Gaode Map API usage, the link is: https://lbs.amap.com/api/webservice/guide/api/weatherinfo Create the account and the API key, then add the relevant parameters to implement the call of the weather API, the application for API Key is as follows: Fig 2 Gaode map API key The following diagram shows the call volume:   Fig 3 Gaode Map API call volume This is the API calling format:   Fig 4 Weather API calling parameters So, the full Gaode Map API link should like this: https://restapi.amap.com/v3/weather/weatherInfo?key=xxxxxxx&city=xxx&extensions=all&output=JSON If need to test the Shanghai weather, city code is 310000. 2.2 Postman test weather API     Postman is an interface testing tool, when doing interface testing, Postman is equivalent to a client, it can simulate various HTTP requests initiated by users, send the request data to the server, obtain the corresponding response results, and verify whether the result data in the response matches the expected value. Postman download link: https://www.postman.com/   After finding the proper weather API platform and the calling link, use the postman do the http GET operation to capture the weather data, refer to the Fig 4, fill the related parameters to the postman: Fig 5 Postman call weather API Send Get command, we can find the weather information in the position 7, the complete all information is: {     "status": "1",     "count": "1",     "info": "OK",     "infocode": "10000",     "forecasts": [         {             "city": "上海市",             "adcode": "310000",             "province": "上海",             "reporttime": "2022-05-27 17:34:12",             "casts": [                 {                     "date": "2022-05-27",                     "week": "5",                     "dayweather": "阴",                     "nightweather": "阴",                     "daytemp": "28",                     "nighttemp": "21",                     "daywind": "东南",                     "nightwind": "东南",                     "daypower": "≤3",                     "nightpower": "≤3"                 },                 {                     "date": "2022-05-28",                     "week": "6",                     "dayweather": "小雨",                     "nightweather": "中雨",                     "daytemp": "24",                     "nighttemp": "20",                     "daywind": "东南",                     "nightwind": "东南",                     "daypower": "≤3",                     "nightpower": "≤3"                 },                 {                     "date": "2022-05-29",                     "week": "7",                     "dayweather": "大雨",                     "nightweather": "小雨",                     "daytemp": "23",                     "nighttemp": "20",                     "daywind": "南",                     "nightwind": "南",                     "daypower": "≤3",                     "nightpower": "≤3"                 },                 {                     "date": "2022-05-30",                     "week": "1",                     "dayweather": "小雨",                     "nightweather": "晴",                     "daytemp": "27",                     "nighttemp": "20",                     "daywind": "北",                     "nightwind": "北",                     "daypower": "≤3",                     "nightpower": "≤3"                 }             ]         }     ] }   We can see, it can capture the continuous 4 days information, with this information, we can get the weather information easily. From the postman, we also can see the Get code, like this: Fig 6 postman API HTTP code     With this API which already passed the testing, it can capture the complete weather information, here, we can consider adding the working http API to the MIMXRT1060-EVK code.    2.3 VIT custom commands     From the maestro code of the RT1060 SDK, we can know that the SDK already supports the VIT library, what is VIT?     VIT's full name: Voice Intelligent Technology, the library provides voice recognition services designed to wake up and recognize specific commands, control IOT, and the smart home. Fig 7 VIT system block diagram     In NXP RT1060 SDK code, the generated wake word and command word have been provided and placed in the VIT_Model.h file. If in the customer's project, how to customize the wake word and command word? With the NXP's efforts, we have made a web page form for customers to choose their own command, and then generate the corresponding VIT_Model.h file for code to call. VIT command word generation web page is: https://vit.nxp.com/#/home     Login the NXP account, choose the RT chip partn umber, wakeup word, voice command. Please note, the current supported RT chip is: RT1060,RT1160,RT1170,RT600,RT500 The following is the example for generating wakeup word and voice command:   Fig 8 Custom VIT configuration Fig 9 generated result Download the generated model, you can get VIT_Model_cn.h, open to see the command word information and related model data stored in the const PL_MEM_ALIGN (PL_UINT8 VIT_Model_cn[], VIT_MODEL_ALIGN_BYTES) array, the command word information is as follows: WakeWord supported : " 小恩 小恩 " Voice Commands supported     Cmd_Id : Cmd_Name       0    : UNKNOWN       1    : 开灯       2    : 关灯       3    : 今天 天气       4    : 明天 天气       5    : 后天 天气 Use the RT1060 SDK maestro_record demo to test this custom command result:   Fig 10 Custom Wakeup word and voice command test From the test result, we can see, both the wakeup word and voice command is detected. 3 Software code 3.1 LWIP socket client code capture weather API From chapter 2.2, we have been able to obtain the weather API and through testing, we can successfully achieve weather acquisition, so we need to add relevant commands in combination with the needs of our own system. For the acquisition of the weather API, the lwip code based on the RT1060 SDK is in the form of socket client. The relevant code is as follows: #define PORT 80 #define IP_ADDR "59.82.9.133" uint8_t get_weather[]= "GET /v3/weather/weatherInfo?key=xxx&city=310000&extensions=all&output=JSON HTTP/1.1\r\nHost: restapi.amap.com\r\n\r\n\r\n\r\n"; if (sys_thread_new("weather_main", weathermain_thread, NULL, HTTPD_STACKSIZE, HTTPD_PRIORITY) == NULL) LWIP_ASSERT("main(): Task creation failed.", 0); static void weathermain_thread(void *arg) { static struct netif netif; ip4_addr_t netif_ipaddr, netif_netmask, netif_gw; ethernetif_config_t enet_config = { .phyHandle = &phyHandle, .macAddress = configMAC_ADDR, }; LWIP_UNUSED_ARG(arg); mdioHandle.resource.csrClock_Hz = EXAMPLE_CLOCK_FREQ; IP4_ADDR(&netif_ipaddr, configIP_ADDR0, configIP_ADDR1, configIP_ADDR2, configIP_ADDR3); IP4_ADDR(&netif_netmask, configNET_MASK0, configNET_MASK1, configNET_MASK2, configNET_MASK3); IP4_ADDR(&netif_gw, configGW_ADDR0, configGW_ADDR1, configGW_ADDR2, configGW_ADDR3); tcpip_init(NULL, NULL); netifapi_netif_add(&netif, &netif_ipaddr, &netif_netmask, &netif_gw, &enet_config, EXAMPLE_NETIF_INIT_FN, tcpip_input); netifapi_netif_set_default(&netif); netifapi_netif_set_up(&netif); PRINTF("\r\n************************************************\r\n"); PRINTF(" TCP client example\r\n"); PRINTF("************************************************\r\n"); PRINTF(" IPv4 Address : %u.%u.%u.%u\r\n", ((u8_t *)&netif_ipaddr)[0], ((u8_t *)&netif_ipaddr)[1], ((u8_t *)&netif_ipaddr)[2], ((u8_t *)&netif_ipaddr)[3]); PRINTF(" IPv4 Subnet mask : %u.%u.%u.%u\r\n", ((u8_t *)&netif_netmask)[0], ((u8_t *)&netif_netmask)[1], ((u8_t *)&netif_netmask)[2], ((u8_t *)&netif_netmask)[3]); PRINTF(" IPv4 Gateway : %u.%u.%u.%u\r\n", ((u8_t *)&netif_gw)[0], ((u8_t *)&netif_gw)[1], ((u8_t *)&netif_gw)[2], ((u8_t *)&netif_gw)[3]); PRINTF("************************************************\r\n"); sys_thread_new("weather", weather_thread, NULL, DEFAULT_THREAD_STACKSIZE, DEFAULT_THREAD_PRIO); vTaskDelete(NULL); } static void weather_thread(void *arg) { int sock = -1,rece; struct sockaddr_in client_addr; char* host_ip; ip4_addr_t dns_ip; err_t err; uint32_t *pSDRAM= pvPortMalloc(BUF_LEN);// host_ip = HOST_NAME; PRINTF("host name : %s , host_ip : %s\r\n",HOST_NAME,host_ip); while(1) { sock = socket(AF_INET, SOCK_STREAM, 0); if (sock < 0) { PRINTF("Socket error\n"); vTaskDelay(10); continue; } client_addr.sin_family = AF_INET; client_addr.sin_port = htons(PORT); client_addr.sin_addr.s_addr = inet_addr(host_ip); memset(&(client_addr.sin_zero), 0, sizeof(client_addr.sin_zero)); if (connect(sock, (struct sockaddr *)&client_addr, sizeof(struct sockaddr)) == -1) { PRINTF("Connect failed!\n"); closesocket(sock); vTaskDelay(10); continue; } PRINTF("Connect to server successful!\r\n"); write(sock,get_weather,sizeof(get_weather)); while (1) { rece = recv(sock, (uint8_t*)pSDRAM, BUF_LEN, 0);//BUF_LEN if (rece <= 0) break; memcpy(weather_data.weather_info, pSDRAM,1500);//max 1457 } Weather_process(); memset(pSDRAM,0,BUF_LEN); closesocket(sock); vTaskDelay(10000); } }  3.2 VIT detect customer command code    Put the generated VIT_Model_cn.h to the maestro_record folder path:   vit\RT1060_CortexM7\Lib    The specific wake word and voice command related code can be viewed from the code vit_pro.c, mainly involving function is: int VIT_Execute(void *arg, void *inputBuffer, int size) The code is modified as follows, mainly to record the wake and wake word number, for specific function control, the command directly controlled here is the local "开灯:turn on the light", "关灯:turn off the light" command, as for the weather command needs to call the socket client API, so in the main lwip call area combined with the command word recognition number to call: if (VIT_DetectionResults == VIT_WW_DETECTED) { PRINTF(" - WakeWord detected \r\n"); weather_data.ww_flag = 1; //kerry } else if (VIT_DetectionResults == VIT_VC_DETECTED) { // Retrieve id of the Voice Command detected // String of the Command can also be retrieved (when WW and CMDs strings are integrated in Model) VIT_Status = VIT_GetVoiceCommandFound(VITHandle, &VoiceCommand); if (VIT_Status != VIT_SUCCESS) { PRINTF("VIT_GetVoiceCommandFound error: %d\r\n", VIT_Status); return VIT_Status; // will stop processing VIT and go directly to MEM free } else { PRINTF(" - Voice Command detected %d", VoiceCommand.Cmd_Id); weather_data.vc_index = VoiceCommand.Cmd_Id;//kerry 1:ledon 2:ledoff 3:today weather 4:tomorrow weather 5:aftertomorrow weather if(weather_data.vc_index == 1)//1 { GPIO_PinWrite(GPIO1, 3, 1U); //pull high PRINTF(" led on!\r\n"); } else if(weather_data.vc_index == 2)//2 { GPIO_PinWrite(GPIO1, 3, 0U); //pull low PRINTF(" led off!\r\n"); } // Retrieve CMD Name: OPTIONAL // Check first if CMD string is present if (VoiceCommand.pCmd_Name != PL_NULL) { PRINTF(" %s\r\n", VoiceCommand.pCmd_Name); } else { PRINTF("\r\n"); } } }  3.3 Voice recognize weather information    In the weather_thread while, check the wakeup word and voice command, if meet the requirement, then create the socket connection, write the API and capture the weather data.   The related code is: while(1) { //add the command request, only cmd == weather flag, then call it. if((weather_data.ww_flag == 1)) { if(weather_data.vc_index >= 3) { // create connection //write API and read API Weather_process(); } memset(weather_data.weather_info, 0, sizeof(weather_data.weather_info)); weather_data.ww_flag = 0; weather_data.vc_index = 0; } vTaskDelay(10000); } void Weather_process(void) { char * datap, *datap1; datap = strstr((char*)weather_data.weather_info,"date"); if(datap != NULL) { memcpy(today_weather, datap,184);//max 1457 if(weather_data.vc_index == 3) { PRINTF("\r\n*******************today weather***********************************\n\r"); PRINTF("%s\r\n",today_weather); return; } } else return; datap1 = strstr(datap+4,"date"); if(datap1 != NULL) { memcpy(tomorr_weather, datap1,184);//max 1457 if(weather_data.vc_index == 4) { PRINTF("\r\n*******************tomorrow weather*******************************\n\r"); PRINTF("%s\r\n",tomorr_weather); return; } } else return; datap = strstr(datap1+4,"date"); if(datap != NULL) { memcpy(aftertom_weather, datap,184);//max 1457 if(weather_data.vc_index == 5) { PRINTF("\r\n*******************after tomorrow weather**************************\n\r"); PRINTF("%s\r\n",aftertom_weather); } } else return; }   Function Weather_process is used to refer to the voice recognized weather number to get the related date’s weather, and printf it. 4 Test result  the test result video: Print the log results as shown in Figure 11, after testing, you can see that the wakeup word and voice command can be successfully recognized, in the recognition of word sequence numbers 3, 4, 5 is the weather acquisition, you can successfully call the lwip socket client API, successfully obtain weather information and printf it.   Fig 11 system test print result  evkmimxrt1060_maestro_weather_backup.zip is the project without sound playback, weather information will print to the terminal! 5 Meet issues conclusion 5.1 LWIP failed to get weather    When creating the code, call the postman provided http code: GET /v3/weather/weatherInfo?key=8f777fc7d867908eebbad7f96a13af10&amp; city=310000&amp; extensions=all&amp; output=JSON HTTP/1.1 Host: restapi.amap.com    Add it to the socket API function: uint8_t get_weather[]= "GET /v3/weather/weatherInfo?key=xxx&amp;city=310000&amp;extensions=all&amp;output=JSON HTTP/1.1\r\nHost: restapi.amap.com\r\n\r\n\r\n\r\n";    The test result is:   Fig 12 socket weather API return issues     We can see, server connection is OK, http also return back the data, but it report the parameter issues, after checking, we use the postman C code, and put it to the get_weather: uint8_t get_weather[]= "GET /v3/weather/weatherInfo?key=xxx&city=310000&extensions=all&output=JSON HTTP/1.1\r\nHost: restapi.amap.com\r\n\r\n\r\n\r\n"; Then, it can capture the weather data, the same as postman test result. 5.2 VIT LWIP merger memory is not enough     After combining the maestro_record and lwip socket code together, compile it, it will meet the DTCM memory overflow issues. Fig 13 memory overflow After optimize, still meet the DTCM overflow issues, so, at last, choose to reconfigure the FlexRAM: OCRAM 192K, DTCM 256K, ITCM 64K Compile it, and the memory overflow issues disappear:   Fig 14 FlexRAM recofiguration 5.3 Print Chinese word in tera    Directly use teraterm, when the weather API returns the Chinese word, the print out information is the garbled code, and then after the following configuration, to achieve Chinese printing: Setup  ->  Terminal Locale    : american->chinese Codepage : 65001 ->936 Fig 15 Tera Term Chinese word print In summary, after various data collection and problem solving, in MIMXRT1060-EVK board  combined with the official SDK complete the function of customizing VIT voice commands to obtain real-time weather and local control.So, even if the ordinary RT series which is not S/L/A/F series, you also can use VIT to implement speech recognition functions. 6 Add the sound broadcast    This chapter mainly gives the method how to add the sound broadcast with the mp3 video data which is stored in the memory, but to the realtime weather data playback, it is not very freely, it needs to check the weather data, and use the video mp3 data lib get the correct mp3 data, as it is not the online TTS method.     So, here, just share one example add the sound broadcast, eg: WW : “小恩小恩”    ->   “小恩来了,请吩咐!” VC  :“今天天气”   ->   “温度32.1度” VC playback is fixed now, if need to play real data, it needs to generate the mp3 voice data lib, then according to the feedback weather information, to generate the correct weather mp3 data array, and play it, as this is a little complicated, but not difficult, so here, just use one fixed sound give an example of it. 6.1 MP3 playback audio data preparation     For audio broadcasting which need to convert the Chinese word into MP3 files, you can use some online speech synthesis software, here use Baidu online speech synthesis function, you can view the previous article, chapter 2.2.2 online speech synthesis: https://community.nxp.com/t5/i-MX-RT-Knowledge-Base/RT106L-S-voice-control-system-based-on-the-Baidu-cloud/ta-p/1363295     If use the Baidu online speech synthesis generated mp3 file to convert to the c array directly, it will meet the first audio play issues, so, here we use the Audacity to convert the mp3 file, the convert configuration is like this:  Fig 16 Audacity convert configuration     After the regeneration of mp3, you can use xxd .exe to convert the mp3 file to an array of C files, and then put it into RT-related memory or external flash , xxd .exe can be found at the following link: https://github.com/baldram/ESP_VS1053_Library/issues/18 The convert command like this: xxd -i your-sound.mp3 ready-to-use-header.c Convert the xiaoencoming.mp3 and temptest.mp3 file to the C array, then modify the data to the C file, save file as: xiaoencoming.h and temptest.h. Here, take xiaoencoming.c as an example: #define XIAOEN_MP3_SIZE  6847 unsigned char xiaoencoming_mp3[XIAOEN_MP3_SIZE] = {   0x49, 0x44, 0x33, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00, 0x21, 0x54, 0x58, …   0x55, 0x55, 0x55, 0x55, 0x55, 0x55, 0x55 }; unsigned int xiaoencoming1_mp3_len = XIAOEN_MP3_SIZE;//6847; Until now, the playback audio data is finished.     Copy xiaoencoming.h and temptest.h to project path: evkmimxrt1060_maestro_weather_mp3\source 6.2 Play the MP3 data from memory    Here, share the related code. 6.2.1 app_streamer.c added code    #include "xiaoencoming.h" #include "temptest.h" void *voice_inBuf = NULL; void *voice_outBuf = NULL; status_t STREAMER_file_Create(streamer_handle_t *handle, char *filename, int eap_par) { STREAMER_CREATE_PARAM params; OsaThreadAttr thread_attr; int ret; ELEMENT_PROPERTY_T prop; MEMSRC_SET_BUFFER_T inBufInfo = {0}; SET_BUFFER_DESC_T outBufInfo = {0}; PRINTF("Kerry test begin!\r\n"); if(filename == "temptest.mp3") inBufInfo = (MEMSRC_SET_BUFFER_T){.location = (int8_t *)temptest_mp3, .size = TEMPtest_MP3_SIZE}; else if(filename == "xiaoencoming.mp3") inBufInfo = (MEMSRC_SET_BUFFER_T){.location = (int8_t *)xiaoencoming_mp3, .size = XIAOEN_MP3_SIZE}; /* Create message process thread */ osa_thread_attr_init(&thread_attr); osa_thread_attr_set_name(&thread_attr, STREAMER_MESSAGE_TASK_NAME); osa_thread_attr_set_stack_size(&thread_attr, STREAMER_MESSAGE_TASK_STACK_SIZE); ret = osa_thread_create(&msg_thread, &thread_attr, STREAMER_MessageTask, (void *)handle); osa_thread_attr_destroy(&thread_attr); if (ERRCODE_NO_ERROR != ret) { return kStatus_Fail; } /* Create streamer */ strcpy(params.out_mq_name, APP_STREAMER_MSG_QUEUE); params.stack_size = STREAMER_TASK_STACK_SIZE; params.pipeline_type = STREAM_PIPELINE_MEM; params.task_name = STREAMER_TASK_NAME; params.in_dev_name = "buffer"; params.out_dev_name = "speaker"; handle->streamer = streamer_create(&params); if (!handle->streamer) { return kStatus_Fail; } prop.prop = PROP_DECODER_DECODER_TYPE; prop.val = (uintptr_t)DECODER_TYPE_MP3; ret = streamer_set_property(handle->streamer, prop, true); if (ret != STREAM_OK) { streamer_destroy(handle->streamer); handle->streamer = NULL; return kStatus_Fail; } prop.prop = PROP_MEMSRC_SET_BUFF; prop.val = (uintptr_t)&inBufInfo; ret = streamer_set_property(handle->streamer, prop, true); if (ret != STREAM_OK) { streamer_destroy(handle->streamer); handle->streamer = NULL; return kStatus_Fail; } handle->audioPlaying = false; error: PRINTF("End STREAMER_file_Create\r\n"); PRINTF("Kerry test end!\r\n"); return kStatus_Success; }   The code implements the thread build, creates a streamer, defines it as playing from memory, decodes the properties for MP3, and specifies an array of MP3 files in memory. Specify a different array of mp3 files in memory based on the calling file name. 6.2.2 cmd.c added code void play_file(char *filename, int eap_par) { STREAMER_Init(); int ret = STREAMER_file_Create(&streamerHandle, filename, eap_par); if (ret != kStatus_Success) { PRINTF("STREAMER_file_Create failed\r\n"); goto file_error; } STREAMER_Start(&streamerHandle); PRINTF("Starting playback\r\n"); file_playing = true; while (streamerHandle.audioPlaying) { osa_time_delay(100); } file_playing = false; file_error: PRINTF("[play_file] Cleanup\r\n"); STREAMER_Destroy(&streamerHandle); osa_time_delay(100); }   Play file, it calls the STREAMER_file_Create API function, start play, and wait the play finished, then release the STREAMER. shellRecMIC API function add the VIT recorded flag, which is used to play feedback audio file. static shell_status_t shellRecMIC(shell_handle_t shellHandle, int32_t argc, char **argv) { … //kerry PRINTF("Kerry MP3 stream data test!\r\n"); PRINTF("---weather_data.ww_flag =%d--\r\n ", weather_data.ww_flag); PRINTF("---weather_data.vc_inde =%d--\r\n ", weather_data.vc_index); PRINTF("---weather_data.mp3_flag =%d--\r\n ", weather_data.mp3_flag); if(weather_data.ww_flag == 1) { play_file("xiaoencoming.mp3", 0); } if(weather_data.vc_index == 3) { play_file("temptest.mp3", 0); } if(weather_data.mp3_flag != 0) { weather_data.ww_flag = 0; weather_data.vc_index = 0; } weather_data.mp3_flag = 0; /* Delay for cleanup */ osa_time_delay(100); return kStatus_SHELL_Success; } If detect the Wakeup Word: “小恩小恩”, play feedback audio: “小恩来了请吩咐”. If detect the voice command: “今天天气”, play feedback audio: “温度32.1度”, please note, this playback just an example, it is the fixed audio, you also can create audio word lib, then according to the received weather information, combine the related word audio together, then playback it. This is a little complicated, but not difficult. So, if need to play the free audio, also can consider the online TTS method in real time. 6.2.3 VIT WW and VC flag VIT_Execute function int VIT_Execute(void *arg, void *inputBuffer, int size) { … if (VIT_DetectionResults == VIT_WW_DETECTED) { PRINTF(" - WakeWord detected \r\n"); weather_data.ww_flag = 1; //kerry weather_data.mp3_flag = 1; } else if (VIT_DetectionResults == VIT_VC_DETECTED) { // Retrieve id of the Voice Command detected // String of the Command can also be retrieved (when WW and CMDs strings are integrated in Model) VIT_Status = VIT_GetVoiceCommandFound(VITHandle, &VoiceCommand); if (VIT_Status != VIT_SUCCESS) { PRINTF("VIT_GetVoiceCommandFound error: %d\r\n", VIT_Status); return VIT_Status; // will stop processing VIT and go directly to MEM free } else { PRINTF(" - Voice Command detected %d", VoiceCommand.Cmd_Id); weather_data.vc_index = VoiceCommand.Cmd_Id;//kerry 1:ledon 2:ledoff 3:today weather 4:tomorrow weather 5:aftertomorrow weather weather_data.mp3_flag = 2; if(weather_data.vc_index == 1)//1 { GPIO_PinWrite(GPIO1, 3, 1U); //pull high PRINTF(" led on!\r\n"); } else if(weather_data.vc_index == 2)//2 { GPIO_PinWrite(GPIO1, 3, 0U); //pull low PRINTF(" led off!\r\n"); } // Retrieve CMD Name: OPTIONAL // Check first if CMD string is present if (VoiceCommand.pCmd_Name != PL_NULL) { PRINTF(" %s\r\n", VoiceCommand.pCmd_Name); } else { PRINTF("\r\n"); } } } return VIT_Status; }   Until now, all the code is added. 6.2.4  playback audio test result     This is the audio playback test result:   Fig 17 playback audio log   From the test result, we can see, we also can use the mp3 data which is stored in the memory and play it as audio playback.   The code project is: evkmimxrt1060_maestro_weather_mp3.zip.  
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There are two new LCD panels that are now available for i.MX RT EVKs: The original RK043FN02H-CT panel is being replaced with the newer RK043FN66HS-CTG panel, which will affect the following EVKs: i.MX RT1050 i.MX RT1060 i.MX RT1064   The original RK055HDMIPI4M panel is being replaced with the newer RK055HDMIPI4MA0 panel, which will affect the following EVKs: i.MX RT595 i.MX RT1160 i.MX RT1170   These changes are due to the previous panels being EOL by the LCD panel manufacturer. These new LCDs have the same dimensions and screen size as their original versions (4.3” 480x272 and 5.5” 720x1280 respectively) and the physical connections are the same. The version name can be found on the back of the LCD. However there are modifications to the software that may need to be made or else the LCD panel will be dark or blank when running MCUXpresso SDK demos on i.MXRT EVKs. This updated code is already available in the latest MCUXpresso SDK and SDK demos are configured by default to use the new panels.   For the i.MX RT1050/1060/1064 panel RK043FN66HS-CTG: The touch controller has changed and the SDK software has been modified to support the new touch controller. The LCD panel also has slightly different specs but the same code used for the original LCD panel will also work with the new LCD panel, so no change is necessary for display-only demos.  LCD demos are configured to support the new panel by default in the latest MCUXpresso SDK. So if you have the original panel you will need to change in the SDK code from      #define DEMO_PANEL  DEMO_PANEL_RK043FN66HS    //new panel (default SDK setting)           to       #define DEMO_PANEL  DEMO_PANEL_RK043FN02H     //older panel   For the i.MX RT595/RT1160/RT1170 panel RK055HDMIPI4MA0: Both the touch and display SDK software had to be updated to support this new panel. LCD demos are configured to support the new panel by default in the latest MCUXpresso SDK. So if you have the original panel you will need to change in the SDK code from:       #define DEMO_PANEL DEMO_PANEL_RK055MHD091    //new panel (default SDK setting)           to       #define DEMO_PANEL DEMO_PANEL_RK055AHD091    //older panel
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This is the recording of the Crossover Code challenge Webinar presented on December 10.
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i.MX RT6xx The RT6xx is a crossover MCU family is a breakthrough product combining the best of MCU and DSP functionality for ultra-low power secure Machine Learning (ML) / Artificial Intelligence (AI) edge processing, performance-intensive far-field voice and immersive 3D audio playback applications. Fig 1 is the block diagram for the i.MX RT600. It consists of a Cortex-M33 core that runs up to 300 MHz with 32KB FlexSPI cache and an optional HiFi4 DSP that runs up to 600MHz with 96KB DSP cache and 128KB DSP TCM. It also contains a cryptography engine and DSP/Math accelerator in the PowerQuad co-processor. The device has 4.5MB on-chip SRAM. Key features include the rich audio peripherals, the high-speed USB with PHY and the advanced on-chip security. There is a Flexcomm peripheral that supports the configuration of numerous UARTs, SPI, I2C, I2S, etc. Fig 1 Create a eIQ (TensorFlow Lite library) demo In the latest version of SDK for the i.MX RT600, it still doesn't contain the demos about the Machine Learning (ML) / Artificial Intelligence (AI), so it needs the developers to create this kind of demo by themself. To implement it, port the eIQ demos cross from i.MX RT1050/1060 to i.MX RT685 is the quickest way. The below presents the steps of creating a eIQ (TensorFlow Lite library) demo. Greate a new C++ project Install SDK library Fig 2 Create a new C++ project using installed SDK Part In the MCUXpresso IDE User Guide, Chapter 5 Creating New Projects using installed SDK Part Support presents how to create a new project, please refer to it for details Porting tensorflow-lite Copy the tensorflow-lite library to the target project Copy the TensorFlow-lite library corresponding files to the target project Fig 3 Add the paths for the above files Fig 4 Fig 5 Fig 6 Porting main code The main() code is from the post: The “Hello World” of TensorFlow Lite Testing On the MIMXRT685 EVK Board (Fig 7), we record the input data: x_value and the inferenced output data: y_value via the Serial Port (Fig 8). Fig 7 Fig 8 In addition, we use Excel to display the received data against our actual values as the below figure shows. Fig 9 In general, In general, it has replicated the result of the The “Hello World” of TensorFlow Lite Troubleshoot In default, the created project doesn't support print float, so it needs to enable this feature by adding below symbols (Fig 10). Fig 10 When a neural network is executed, the results of one layer are fed into subsequent operations and so must be kept around for some time. The lifetimes of these activation layers vary depending on their position in the graph, and the memory size needed for each is controlled by the shape of the array that a layer writes out. These variations mean that it’s necessary to calculate a plan over time to fit all these temporary buffers into as small an area of memory as possible. Currently, this is done when the model is first loaded by the interpreter, so if the area is not big enough, you’ll see a crash event happen. Regard to this application demo, the default heap size is 4 KB, obviously, it's not big enough to store the model’s input, output, and intermediate tensors, as the codes will be stuck at hard-fault interrupt function (Fig 11). Fig 11 So, how large should we allocate the heap area? That’s a good question. Unfortunately, there’s not a simple answer. Different model architectures have different sizes and numbers of input, output, and intermediate tensors, so it’s difficult to know how much memory we’ll need. The number doesn’t need to be exact—we can reserve more memory than we need—but since microcontrollers have limited RAM, we should keep it as small as possible so there’s space for the rest of our program. We can do this through trial and error. For this application demo, the code works well after increasing ten times than the previous heap size (Fig 12). Fig 12
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One-stop secure boot tool: NXP-MCUBootUtility v1.0.0 is released Source code: https://github.com/JayHeng/NXP-MCUBootUtility 【v1.1.0】 Feature:   1. Support i.MXRT1015   2. Add Language option in Menu/View and support Chinese Improvement:   1. USB device auto-detection can be disabled   2. Original image can be a bootable image (with IVT&BootData/DCD)   3. Show boot sequence page dynamically according to action Interest:   1. Add sound effect (Mario) 【v1.2.0】 Feature:   1. Can generate .sb file for MfgTool and RT-Flash   2. Can show cost time along with gauge Improvement:   1. Non-XIP image can also be supported for BEE Encryption case   2. Display guage in real time Bug:   1. Region count cannot be set more than 1 for Fixed OTPMK Key case   2. Option1 field is not implemented for FlexSPI NOR configuration
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The MIMXRT1050-EVK includes a CMSIS-DAP/DAP-Link interface that includes MSD drag and drop functionality for the HyperFlash on the board. The drag and drop programming functionality can be used to program applications compiled to execute-in-place (XIP) from the HyperFlash memory. In the early SDK versions for RT1050, the projects did not include the flash configuration block and IVT required to make a bootable image across all toolchains. Starting with the SDK 2.3.1 release, projects include XIP files that add this information to the project. This allows for programming a bootable application to the external flash memory directly from the debugger, so many customers might not even need to use the drag-and-drop programming feature any more. Because of the SDK changes, the DAP-Link application has also had changes: Early versions of the DAPLink firmware were setup to work with a raw application binary like those generated by the SDK 2.3.0 for toolchains other than the MCUXpresso IDE. These versions will take the raw application binary and prepend the flash configuration block for the HyperFlash/QSPI and an IVT to make a bootable image. Newer version of the DAPLink firmware are setup to work with a complete bootable binary like those generated by SDK 2.3.1 and later. These versions will not attempt to prepend a flash configuration block and IVT to the application, because these are assumed to already be present. The following table describes the versions of the DAPLink application that have been released. NOTE: the firmware can be updated on the board, so the version on a given board might not match what was originally programmed at manufacture time. The latest version of firmware can be downloaded from www.nxp.com/opensda Board Rev DAPLink MCU GIT SHA from details.txt file NOTE EVK_A2 MK20 34182e2cce4ca99073443ef29fbcfaab9e18caec DAPLink will add FCB and IVT EVK_A3-EVK-A5 MK20 853df431d81359e822f49363891f877f17d31efb DAPLink will add FCB and IVT EVKB_A MK20 853df431d81359e822f49363891f877f17d31efb DAPLink will add FCB and IVT EVKB_A1 MK20 853df431d81359e822f49363891f877f17d31efb DAPLink will add FCB and IVT EVKB_A1 MK20 b3435dbed0ba4f09680e49d2fcfdaab32c7a4c71 DAPLink will NOT add FCB and IVT To use the drag and drop programming: 1. Configure the board for serial downloader mode by setting SW7 to OFF-ON-OFF-ON.  2. Press SW3 to reset the processor. 3. Drag the application binary to the RT1050-EVK drive.  4. Put the board back in internal boot mode by setting SW7 to OFF-ON-ON-OFF. 5. Press SW3 to reset the processor and your application should boot.  There are some limitations to the drag and drop programming to keep in mind: - Only works for Hyperflash/QSPI XIP applications. Doesn't support copying the code from HyperFlash to another memory (like ITCM) for execution - Application initial stack pointer must be located in DTCM - Doesn't support DCD files The flashloader and ROM tools offer a second external memory programming method where the limitations above do not apply: https://www.nxp.com/downloads/en/initialization-boot-device-driver-code-generation/Flashloader_i.MXRT1050_1.0_GA.zip  Refer to AN12107 for more information: https://www.nxp.com/docs/en/application-note/AN12107.pdf?fsrch=1&sr=2&pageNum=1 
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In the i.MXRT 1050 EVK web page, there is a very nice "Getting Started" page to show the videos and steps how to use the board. 1. Connect the board to your PC by a USB cable. 2. Build and download the SDK. a. In the SDK Builder web page, you can customize and download the specific SDK of your board. b. On the next page, you can select different OS and different IDE. Select "MCUpresso IDE" for Windows here. c. You can add the software component that you wanted. d. Request to build the SDK. e. When the build request has completed, the SDK is available for download under the SDK Dashboard page. - Download icon : Download the SDK - Rebuild icon : Rebuild the SDK with different setting - Share icon : Share the SDK to others - MCUConfigTool icon : Run the MCU Configuration Tool to configure the pinmux and clocks for your own design board. - Remove icon : Remove the SDK from the Dashboard. 3. Install the MCUXpresso IDE. a. Go to the MCUXpresso IDE weg page to download the IDE and then install it. 4. Build and run the example on EVK. a. Open the MCUXpresso IDE. Simply drag & drop the SDK zip file to "Installed SDKs" view. b. Import the SDK examples and then click "Next". c. Select the "hello_world" under the demo_apps. d. Click "Build" to build the demo. e. Execute the terminal software (e.g. PuTTY). The COM port of the console output can be found in "devices manager". The COM setting is 115200,8,N,1. f. Click the "bug" icon to start the debugging. g. Click "Resume All Debug Sessions" icon to run the demo. h. "hello world" print out in console. Reference: i.MXRT1050 web page ( Contain the datasheet, reference manual of the i.MXRT1050 processor) i.MXRT1050EVK web page ( Contain the user's guides of the i.MXRT1050 EVK) MCUXpresso IDE web page ( Contain the user's guides of the MCUXpresso IDE )
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1.1 Introduction   RT-Flash is a GUI tool specially designed for i.MX RT production. Its feature is similar to MfgTool2, but it solves below limitaions of MfgTool2: The .sb file can only be specified in xml file; USB port is the only choice to download .sb file; Sometimes USB Hub is required to connect;   With RT-Flash, you can easily get started with NXP MCU secure boot. The main features of RT-Flash include: Support i.MXRT1015, i.MXRT1021, i.MXRT1051/1052, i.MXRT1061/1062, i.MXRT1064 SIP Support both UART and USB-HID serial downloader modes Support for loading .sb image file into boot device 1.2 Download   RT-Flash is developed in Python, and it is open source. The development environment is Python 2.7.15 (32bit), wxPython 4.0.3, pySerial 3.4, pywinusb 0.4.2, PyInstaller 3.3.1 (or higher). Source code: https://github.com/JayHeng/RT-Flash   RT-Flash is packaged by PyInstaller, all Python dependencies have been packaged into an executable file (\RT-Flash\bin\RT-Flash.exe), so if you do not want to develop RT-Flash for new feature, there is no need to install any Python software or related libraries. Note1: The RT-Flash.exe in the source code package is packaged in the Windows 10 x64 environment and has only been tested in this environment. If it cannot be used directly for system environment reasons, you need to install Python2.7.15 x86 version (Confirm that the directory "\Python27" and "\Python27\Scripts" are in the system environment variable path after the installation is completed), then click on "do_setup_by_pip.bat" in the "\RT-Flash\env" directory to install the Python library on which RT-Flash depends. Finally, click "do_pack_by_pyinstaller.bat" to regenerate the RT-Flash.exe. Note2: You must use Python2 x86 version, because RT-Flash uses the pywinusb library, which cannot be packaged by PyInstaller in Python2 x64 version. The pywinusb author has no plan to fix the problem. 1.3 Installation   RT-Flash is a pure green free installation tool. After downloading the source code package, double-click "\RT-Flash\bin\RT-Flash.exe" to use it. No additional software is required.   Before the RT-Flash.exe graphical interface is displayed, a console window will pop up first. The console will work along with the RT-Flash.exe graphical interface. The console is mainly for the purpose of showing error information of RT-Flash.exe. At present, RT-Flash is still in development stage, and the console will be removed when the RT-Flash is fully validated. 1.4 Interface
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There are two main methods for importing a project from GUI Guider to MCUXpresso: Linking the whole GUI Guider project into MCUXpresso. Copying and replacing the GUI on a pre-built LVGL project on MCUXpresso (like the "lvgl_guider" SDK example code). Although the first method is quite convenient, there are times when a user might have a GUI already on an established project. In this case, the second method might be very useful. However, when trying to add lottie widgets to a GUI of an already established project (like the "lvgl_guider" SDK example code), extra steps are required, as this widget uses a proprietary library from Samsung which requires extra steps to add and enable. This document describes the steps needed to add rlottie widgets to a project that is already established in MCUXpresso. GUI Guider 1.8.0, MCUXpresso v11.10.0 and SDK 2.16.000 were used for this document, although the process should be the same for future versions.   Once the Lottie widget has been added to the GUI on GUI Guider, you will want to follow the common steps to import this GUI into the MCUXPresso project. Replace the "custom" and "generated" folders on the MCUXpresso project with the GUI Guider folders: <GUI Guider Project Installation>\custom. <GUI Guider Project Installation>\generated.   TIP: You can open the default location of the MCUXpresso project on the file explorer by selecting the project, opening the "Show In" window by pressing Alt + Shift + W, and selecting "System Explorer":   TIP: You can open the default location of the GUI Guider project on the file explorer by clicking on the green folder icon on the top menu bar:   Copy the "lib" folder from: <GUI Guider Project Installation>\lib into the MCUXpresso project.   Copy the "rlottie" folder from: <GUI Guider Project Installation>\sdk\core\rlottie into the MCUXpresso project.   That’s it for file management. Now, in MCUXpresso: Include the "lib" and "rlottie" folders as source folders by adding their path under: Project properties > C/C++ General > Paths and Symbols > Source Location.   Include the rlottie folder as include path by adding its path under the following two compilers' include paths: Project properties > C/C++ Build > Settings > MCU C++ Compiler > Includes > Include Paths.   Project properties > C/C++ Build > Settings > MCU C Compiler > Includes > Include Paths.   As mentioned on the LVGL documentation for "Rlottie player", we need to add the "-rlottie" flag to the linker, but also link the rlottie library (librlottie.a) to the project. This is done by setting the following on Project Properties > C/C++ Build > Settings > MCU C++ Linker > Libraries:   Finally, enable the macro definition: #define LV_USE_RLOTTIE 1 under the "lv_conf.h" file on "source" to tell LVGL that we are using the rlottie library.   With these steps, the rlottie application was imported, along with its headers and libraries, and this rlottie feature was enabled by linking them to the build configuration. Because of this, the application compiles without any errors. Great! Note: There's a possibility that the following error shows up when compiling: If this is the case, simply change the following macro in "source" > "lv_conf.h" from '0' to '1' to enable user data in the lv_font_t variable type:   However, when executing the application, the screen goes black. Turns out, as soon as the application tries to execute the first rlottie instruction from the ".a" archived library, it is unable to execute anything, which causes the application to halt and get stuck on a black screen. This happens as soon as the application calls line 113 of the "lv_rlottie.c" file to construct the rlottie widget: (This file is under <project folder>\lvgl\lvgl\src\extra\libs\rlottie)   But there was no issue when building the application, so what gives? Well, the Rlottie library is quite memory heavy, so we also need to provide it with memory according to its requirements. We can do this by increasing the heap and stack size from their "default" state to something like 0x800000 for the stack and 0x1000 for the heap. These values are what GUI Guider provides to its projects when using Rlottie widgets.   With this, the MCUXpresso project will now have the rlottie libraries enabled, and also have enough memory to successfully debug/run the project on the i.MX RT board.       Happy "Lottie-ing"!   Edwin.
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How to load MDK RAM app to the RT1170 external flash 1. Abstract This guide is requested by our end customer, he wants to realize the MDK project RAM code download to the MIMXRT1170 external QSPI flash. So, based on the NXP RT1170 SDK, and the MIMXRT1170-EVK board, generate the MDK project, reallocate the app image, generate the image, and use the tool to download the code to the external flash. 2. App image prepare 2.1 Generate one SDK MDK standalone project Open the SDK_2_15_000_MIMXRT1170-EVK webpage: https://mcuxpresso.nxp.com/en/builder?hw=MIMXRT1170-EVK Download the SDK, and generate one MDK standalone project: Fig 1 Fig 2 After downloading, we will get the MIMXRT1170-EVK-iled_blinky_cm7.zip, which is the MDK project. 2.2 MDK project image reallocation As the RAM image is the none-xip image, normally to the IDE, can’t download to the flash directly, as the debug is in the RAM. If want to download to the flash, we can generate the app image, then use the tool to program it to the external flash. Normally, none-xip image, the IVT offset is 0X400, so we need to reallocate the image start address, here, we can use 0X2000 as the app entry address. Fig 3 ITCM default size is 256K=0X4000, so modify the linker file-> scf file like this: Fig 4 Now, to generate the hex and bin image file, which is used for the tool downloading. Fig 5 To build the bin file command: $K\ARM\ARMCC\bin\fromelf.exe --bin --output=debug\@L.bin !L Fig 6   Building, you can find the file in the folder: MIMXRT1170-EVK-iled_blinky_cm7\iled_blinky_cm7\debug Fig 7 2.3 MDK project debug after reallocation After the image reallocation, some customer may still need the MDK RAM project can do the debugging, here, also need to modify the debug .ini file. The Setup also need to change the SP, PC and Vector table offset register address. Fig 8 Then build and debug the code, we can find it can enter the ram image debug mode: Fig 9 3. App image download We can use the MCUBootUtility Tool to download the code: https://github.com/JayHeng/NXP-MCUBootUtility/releases/tag/v6.1.0 the related user manual is: https://github.com/JayHeng/NXP-MCUBootUtility Download the tool. MIMXRT1170-EVK enter the serial download mode by changing SW1: 1-OFF,2-OFF,3-OFF,4-ON Power off and power on the board again, find another USB cable to connect the J20 USB1 interface. Then, use the MCUBootutility to connect the board: Fig 10 After connection, select the MDK project generated .hex file: Fig 11 Press the All-in-One-Action button, to download the code, this is the downloaded result: Fig 12 Press the “Reset device” button to exit the tool. Then MIMXRT1170-EVK board change SW1: 1-OFF, 2-OFF, 3-ON,4-OFF Press the EVK on board reset button, SW4, you will find the LED is blinking, it means the MDK RAM project already download to the external QSPI flash, and boot OK.
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This demo code shows how to synchronize the PWM signals with another internal timer or an off-chip source. It allows you to achieve slower PWM frequencies than those that can be achieved with internal clocks as well as that multiple modules and multiple chips can be synchronized to each other. The idea is the following: The QTMR generates a PWM signal (external clock signal) which is routed through the XBAR to clocking the eFlexPWM, and at the same, the external clock signal is routed to an IO PAD in the first MCU. In a second MCU, an IO PAD is routed through the XBAR to clocking the eFlexPWM (see Figure 1).   Figure 1     The demo code (only MCU1 part so far) can me tested using the SDK for EVKB-IMXRT1050 v2.14.0. Probe the PWM signals using an oscilloscope: - At J24-1  GPIO_AD_B0_03  XBAR1_INOUT17 (QTMR PWM signal) - At J24-6  GPIO_SD_B0_00  FLEXPWM1_PWM0_A - At J24-3  GPIO_SD_B0_01  FLEXPWM1_PWM0_B Please remember weld resistors 0Ω at R280 R281.
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RT1170 Boundary Scan test based on lauterbach   1. Abstract Boundary Scan is a method of testing interconnections on circuit boards or internal sub-blocks of circuits. You can also debug and observe the pin status of the integrated circuit, measure the voltage or analyze the sub-modules inside the integrated circuit, and test based on the JTAG interface. NXP officials have provided two good application notes: AN13507 (LPC) and AN12919 (RT). Based on the reference application note test method, this article provides the boundary scan test results for NXP MIMXRT1170-EVK revC1. It can use Lauterbach to connect the chip and perform boundary scan to control the external pins. A script file is also provided. It can realize one-click connection to boundary scan and achieve level control of external pins. 2. RT1170 test details   2.1 Hardware platform Lauterbach:LA3050 MIMXRT1170-EVK rev C1: The hardware modification point is to remove the onboard resistors R187, R208, R195 and R78. The purpose is that J6 prohibits external circuits from interfering with JTAG related pins. Disconnect J5, J6, J7, J8, that is, disconnect the onboard debugger, and use an external Lauterbach connection to J1. The connection situation is as follows: Fig 1 RT1170 directly supports both SWD and JTAG by default, so unlike RT10XX which needs to modify the fuse to convert from SWD to JTAG, RT1170 can directly use the JTAG interface.   2.2 Software operation Download Lauderbach's supporting software and install it. After installation, open the TRACE32 ICD Arm USB. If the Lauderbach device is connected, the interface will open successfully. Fig 2 At this time, you can enter the relevant commands in the yellow box in the picture above. Here you need to prepare the .bsdl file of the chip, which is usually placed on the chip introduction page of nxp.com. For example, the link to the bsdl file of RT1170 is: https://www.nxp.com/downloads/en/bsdl/i.MXRT1170_BDSL.bsdl You can copy the i.MXRT1170_BSDL.bsdl file to the Lauderbach installation path: C:\T32 Next, enter the following command in the window to open the boundary scan window and the i.MXRT1170_BSDL.bsdl file: SYStem.Mode Down BSDL.RESet BSDL.ParkState Select-DR-Scan BSDL.state Here, it will open the window: Fig 3 Click FILE item, input the downloaded i.MXRT1170_BSDL.bsdl, then in the window.,input the commander: BSDL.SOFTRESET Fig 4 Click check->BYPASSall,IDCODEall,SAMPLEall, make sure the 3 methods can be passed. Fig 5 Fig 6 Fig 7 To test the output control situation, it need to do the following operation: BSDLSET 1.: instructions->EXTEXT, DR mode->Set Write, Fileter data->uncheck intern BSDL.state->Run: check SetAndRun, TwoStepDR, Click RUN. BSDLSET 1. Can control the related pins, eg, GPIO_AD_26 is on the on board D34 LED. 1 ON,0 OFF. Fig 8   2.3 Automation control command script As can be seen from Section 2.2, single-step operation requires manual typing of commands. In actual testing, the efficiency is very low, so scripting language can be used to directly implement automated command control. Below, taking RT1170 as an example, we provide a script to control the on-board D34 light on and off. In this way, when the TRACE32 software is opened, you only need to open the script directly, enter the debug mode, run it to the end with one click, and check the on-board light control status. Script language file, the suffix is .cmm, step: File->New Script, enter the following script command: ;system setup SYStem.Mode Down SYStem.CPU CortexM7 SYSTEM.CONFIG.DEBUGPORTTYPE JTAG SYStem.JtagClock 1MHz ;BSDL Settings BSDL.RESet BSDL.ParkState Select-DR-Scan BSDL.state ;configure boundary scan chain BSDL.FILE i.MXRT1170_BDSL.bsdl ;Check boundary scan chain BSDL.SOFTRESET BSDL.BYPASSall BSDL.IDCODEall BSDL.SAMPLEall ;Perform Sample test BSDL.RUN BSDL.SetAndRun ON BSDL.TwoStepDR ON BSDL.SET 1. BSDL.SET 1. IR EXTEST BSDL.SET 1. PORT GPIO_AD_26 0 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 1 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 0 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 1 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 0 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 1 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 0 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 1 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 0 WAIT 1.s BSDL.SET 1. PORT GPIO_AD_26 1 WAIT 1.s Function, the led will be blinking 5 times, duration is 1s. Save the script, then debug it. Fig 9 This is the video for the testing:   It can be seen that the onboard light D34 can automatically flash, indicating that the BSDL automatic test has been completed so far.          
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RT1050 FlexIO OV7670 with TFT LCDdisplay 1 Abstract Regarding the RT10XX flexIO collecting OV7670 camera data and displaying it on TFT LCD, in fact, the NXP official website has a very good application note AN12686, but the test is based on RT1010 and not EVK. It may be difficult for actual customers to test directly. When the author was supporting customers, I encountered customers who wanted to implement flexIO on RT1050 EVK to collect parallel port OV7670 data and display it on TFT LCD, which is the LCD with SPI interface, so this article gives the specific test results of the finished product, RT1050 flexIO and There are some differences between RT1010 flexIO. RT1010 flexIO has 8 shifters, but RT1050 only has 4 shifters, so some code modifications need to be made and transplanted to RT1050. Since it is going to run on MIMXRT1050-EVKB, you also need to consider the flexIO pins that can be used, modify the EVKB, and manually weld the relevant pins to configure the corresponding camera signals and LCD display signals. This article mainly comes from problems encountered by customers during testing, so it provides specific hardware connections, software code sharing, test finished product results, etc. 2. Software and hardware prepare Since AN12686 has given the principle in great detail, this article aims to give the differences and the specific conditions of working on RT1050-EVKB. 2.1 Hardware configuration The platform is based on MIMXRT1050-EVKB revA1, OV7670 module, 2.4-inch TFT LCD LCD SPI serial touch TFT color screen ILI9321, with a resolution of 240*320.     For the OV7670 module status and pin status, please check the article:    RT1050 CSI OV7670 camera eLCD display The camera module pins are as follows: Fig 1    TFT LCD picture: Fig 2 Pin No Signal Description 1 GND Power ground 2 VCC Power 3.3V 3 CLK SPI clock 4 MOSI SPI data 5 RES LCD reset 6 DC LCD data/commander select pin 7 BLK Backlight control switch, backlight is turned on by default, low level turns off the backlight 8 MISO Touch data reading 9 CS1 Display selection pin 10 CS2 Touch selection pin 11 PEN Touch interrupt signal For LCD, this article only uses the display part and does not use the rough mold part. Considering the pin layout of MIMXRT1050-EVKB, the application note flexIO1 is not used here, but FlexIO2 is selected. The actual RT1050-EVKB and OV7670 module and LCD connection pins are given below. The connection between the LCD signal pin and the MCU MIMXRT1050-EVKB RevA1 signal pin is as follows: LCD signal and pin MIMXRT1050-EVKB revA1 signal and pin GND P1 GND J24_7 3.3V VCC P2 3.3V J24_8 CLK P3 GPIO_AD_B1_15(SPI3_CLK) R98 MOSI P4 GPIO_AD_B1_14(SPI3_MOSI) R99 RES P5 GPIO_AD_B0_02(GPIO1_IO02) J24_2 DC P6 GPIO_AD_B1_10(GPIO01_IO26) J23_1 CS1 P9 GPIO_AD_B1_12(GPIO01_IO28) R100   OV7670 signal pin and MCU MIMXRT1050-EVKB RevA1 signal pin connection situation: 0V7670 signal and pin MIMXRT1050-EVKB revA1 signal and pin OV7670_D0 P3 GPIO_B0_05(FLEXIO2_D05) SW5_1 OV7670_D1 P4 GPIO_B0_06(FLEXIO2_D06) SW5.2 OV7670_D2 P5 GPIO_B0_07(FLEXIO2_D07) SW5_3 OV7670_D3 P6 GPIO_B0_08(FLEXIO2_D08) SW5_4 OV7670_D4 P7 GPIO_B0_09(FLEXIO2_D09) SW6_1 OV7670_D5 P8 GPIO_B0_10(FLEXIO2_D10) SW7_1 OV7670_D6 P9 GPIO_B0_11(FLEXIO2_D11) SW6_2 OV7670_D7 P10 GPIO_B0_12(FLEXIO2_D12) SW6_3 XCLK P11 GPIO_B0_13(FLEXIO2_D13) SW7_2 PCLK P12 GPIO_B0_14(FLEXIO2_D14) SW6_4 HREF(HS) P13 GPIO_B0_15(FLEXIO2_D15) R258/R324 VSYNC P14 GPIO_AD_B0_03(GPIO01_03) J24_1 I2C_SDA P15 GPIO_AD_B1_01(I2C1_SDA) J23_5 I2C_SCL P16 GPIO_AD_B1_00(I2C1_SCLK) J23_6 PWDN P1 GPIO_AD_B1_02(GPIO1_IO18) J22_7 RESET P2 GPIO_AD_B1_03(GPIO1_IO19) J22_8 3.3V P18 3.3V J22_7 GND P17 GND J22_8 In order to reduce the impact of the signal, MIMXRT1050-EVKB removes R323, R316, R309, and D6 on the board. The physical connection situation is as follows: Fig 3 2.2 Software configuration Since the flexIO of RT1050 is different from the 8 shifters of RT1010, the DMA configuration needs to be modified. The difference code of flexio_ov7670 is as follows:   static FLEXIO_CAMERA_Type s_FlexioCameraDevice = { .flexioBase = BOARD_CAMERA_FLEXIO_INST, .datPinStartIdx = BOARD_CAMERA_FLEXIO_DATA_PIN_START_INDEX, .pclkPinIdx = BOARD_CAMERA_FLEXIO_PCLK_PIN_INDEX, .hrefPinIdx = BOARD_CAMERA_FLEXIO_HREF_PIN_INDEX, .shifterStartIdx = 0U, .shifterCount = 4, .timerIdx = 0U, }; static void configDMA(void) { uint32_t soff, smod = 0u, size=0u; while(1u << size < DMA_TRSF_SIZE) /* size = log2(DMA_TRSF_SIZE) */ { size++; } if(DMA_TRSF_SIZE == DMA_MINOR_LOOP_SIZE) { soff = 0u; } else { soff = DMA_TRSF_SIZE; while(1u << smod < DMA_MINOR_LOOP_SIZE) /* smod = log2(DMA_MINOR_LOOP_SIZE) */ { smod++; } } /* Configure DMA TCD */ DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].SADDR = FLEXIO_CAMERA_GetRxBufferAddress(&s_FlexioCameraDevice); DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].SOFF = soff; DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].ATTR = DMA_ATTR_SMOD(smod) | DMA_ATTR_SSIZE(size) | DMA_ATTR_DMOD(0u) | DMA_ATTR_DSIZE(size); DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].NBYTES_MLNO = 16; DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].SLAST = 0u; DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].DADDR = (uint32_t)(*pFlexioCameraFrameBuffer); DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].DOFF = 8; DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].CITER_ELINKNO = DMA_MAJOR_LOOP_SIZE; DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].DLAST_SGA = -OV7670_FRAME_BYTES; DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].CSR = 0u; DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].CSR |= DMA_CSR_DREQ_MASK; DMA0->TCD[FLEXIO_CAMERA_DMA_CHN].BITER_ELINKNO = DMA_MAJOR_LOOP_SIZE; /* Configure DMA MUX Source */ DMAMUX->CHCFG[FLEXIO_CAMERA_DMA_CHN] = DMAMUX->CHCFG[FLEXIO_CAMERA_DMA_CHN] & (~DMAMUX_CHCFG_SOURCE_MASK) | DMAMUX_CHCFG_SOURCE(FLEXIO_CAMERA_DMA_MUX_SRC); /* Enable DMA channel. */ DMAMUX->CHCFG[FLEXIO_CAMERA_DMA_CHN] |= DMAMUX_CHCFG_ENBL_MASK; } The code structure adopts: the camera uses flexIO mode to collect DMA transfer. After collecting one frame, DMA stores the data into the buffer, and then displays one frame of data uniformly on the LCD. Since there are many configuration codes for flexIO OV7670 and LCD SPI, we will not explain them one by one here. Please check the attached code source code for details. There is a header file of horsepic.h in the code. This file is a 320*240 RGB565 picture of a horse. It is used to test the LCD display separately. Usually after connecting the LCD, you need to test the LCD display separately. You can use a fixed picture to get the display. , here is the method of converting the picture into a C array: First adjust the picture to the LCD resolution size, and then convert it through the LVGL online conversion tool, select CF_RGB565A8, but the RGB565 generated by this format will have 1 more byte each, you can do it yourself After deletion, it can be called by code: https://lvgl.io/tools/imageconverter Display horse picture code: convert8to16(); ILI9341_FillPic(0, 0, OV7670_FRAME_WIDTH-1u, OV7670_FRAME_HEIGHT-1u, (uint16_t *)(horse16)); Display result: Fig 4 3 Test result and summarize    About RT1050-EVKB, use flexIO to collect OV7670 data and display the situation through TFT LCD. Please check the video for the specific code situation. Check the attached source code. You can see from the video results that the flexIO OV7670 camera data can be successfully displayed and the code can successfully run the function.
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  RT1050 CSI OV7670 camera eLCD display 1.Abstract OV7670 is a CMOS VGA image sensor with small size and low operating voltage. It is controlled by the SCCB bus and can output 8-bit image data of various resolutions with a frame rate of up to 30 frames/second and low cost. This article mainly implements the use of CSI on RT10XX to obtain OV7670 camera data, and displays it using the eLCDIF display module that comes with RT10XX. The camera and display use RGB565 format. The camera resolution configuration is QVGA 320*240, the LCD is NXP official EVKB matching LCD RK043FN02H, the resolution is 480*272, and the frame rate is 30FPS. This article is based on NXP official RT1050 SDK: SDK_2_14_0_EVKB-IMXRT1050\boards\evkbimxrt1050\driver_examples\csi\rgb565 Porting the OV7670 driver to implement the CSI method to collect OV7670 image data and display it on the LCD through the eLCDIF module   2. Principle explanation    Here is a brief explanation of relevant knowledge. 2.1 RGB565 Color mode As a basic color coding format for images, RGB565 refers to a pixel that occupies 2 bytes of data and is usually used in images and display devices. R red, G green, B blue, the actual display can obtain different other colors according to the configuration of the three primary colors. Each pixel bit can display 65536 (2^16) colors. The specific allocation is as follows:   Fig 1 From the above figure, we can know that the 2-byte data displayed in pure red, green and blue is: Red: 0xf800, Green: 0X07E0, Blue: 0X001F 2.2 OV7670 camera hardware and waveform situation The OV7670 module used is as follows: Fig 2 Pin situation No Signal Description 1 PWDN Power consumption selection mode, pull down for normal use 2 RET Reset port, pull high for normal use 3 D0 Data port output bit 0 4 D1 Data port output bit 1 5 D2 Data port output bit 2 6 D3 Data port output bit 3 7 D4 Data port output bit 4 8 D5 Data port output bit 5 9 D6 Data port output bit 6 10 D7 Data port output bit 7 11 XLK Clock signal input signal 12 PLK Pixel clock output signal 13 HS Horizontal synchronization signal output signal 14 VS Frame sync clock output signal 15 SDA SCCB Interface data control 16 SCL SCCB Interface clock control 17 GND GND 18 3.3V 3.3V power RGB565 output data timing: Fig 3 2.2 CSI frame synchronization signal timing waveform Fig 4 2.3 LCD display wave Fig 5 Therefore, the data of OV7670 is obtained through CSI and then stored in the buffer. The eLCDIF then retrieves the data from the buffer and displays it on the LCD screen to display the real-time collection and reality of the camera data. 3 Software and hardware realize    The test platform is based on NXP MIMXRT1050-EVKB revA1 version: https://www.nxp.com/design/development-boards/i-mx-evaluation-and-development-boards/i-mx-rt1050-evaluation-kit:MIMXRT1050-EVK LCD为:https://www.nxp.com/part/RK043FN02H-CT#/ 3.1 Hardware connection As can be seen from Figure 2, the universal module purchased is a 2.54mm direct plug mode, but the CSI interface used on the MIMXRT1050-EVKB board is an FPC interface, so an adapter board is required to switch from FPC to 2.54mm direct plug mode. The wiring diagram is as follows:    Fig 6 The actual overall hardware connection situation is as follows: Fig 7 3.2 Software prepare Regarding the SDK driver of OV7670, the RT SDK does not provide it directly, but the FRDM-K82 SDK provides relevant drivers that can be transplanted to the RT1050 SDK.       SDK version:SDK_2_14_0_EVKB-IMXRT1050\boards\evkbimxrt1050\driver_examples\csi\rgb565 The code replaces the original OV7725 code, replaces the relevant driver with the OV7670 driver, modifies the OV7670 code, matches it to the RT1050 CSI code, and adds IO signal control for OV7670 RST and PWDN. The reason for adding RST and PWDN control is that it was found Some modules, if the RST pin is not closed and delayed to open, will cause the problem of unsuccessful acquisition. However, with the addition of RST and PWDN control, currently OV7670 from different manufacturers can successfully acquire and display stably. For the specific OV7670 code, you can view the attached source code. The camera initialization code is as follows:   static void APP_InitCamera(void) { const camera_config_t cameraConfig = { .pixelFormat = kVIDEO_PixelFormatRGB565, .bytesPerPixel = APP_BPP, .resolution = FSL_VIDEO_RESOLUTION(320, 240), /* Set the camera buffer stride according to panel, so that if * camera resoution is smaller than display, it can still be shown * correct in the screen. */ .frameBufferLinePitch_Bytes = DEMO_BUFFER_WIDTH * APP_BPP, .interface = kCAMERA_InterfaceGatedClock, .controlFlags = DEMO_CAMERA_CONTROL_FLAGS, .framePerSec = 30, }; memset(s_frameBuffer, 0, sizeof(s_frameBuffer)); BOARD_InitCameraResource(); CAMERA_RECEIVER_Init(&cameraReceiver, &cameraConfig, NULL, NULL); if (kStatus_Success != CAMERA_DEVICE_Init(&cameraDevice, &cameraConfig)) { PRINTF("Camera device initialization failed\r\n"); while (1) { ; } } CAMERA_DEVICE_Start(&cameraDevice); /* Submit the empty frame buffers to buffer queue. */ for (uint32_t i = 0; i < APP_FRAME_BUFFER_COUNT; i++) { CAMERA_RECEIVER_SubmitEmptyBuffer(&cameraReceiver, (uint32_t)(s_frameBuffer[i])); } } The resolution here is QVGA 320*240, which does not match the 480*272 of the LCD, but it does not matter. In fact, the size of 320*240 is displayed in the LCD. If you want to display it to 480*272, you can also configure the size through PXP. For more code details, see the attached code package. 4. Summary This article aims to provide a demo of RT OV7670 CSI+eLCDIF acquisition and display. let’s go directly to the finished product effect video. You can see that the relative display is relatively clear, and the refresh effect is also good.
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